From f4fa9881afa2816c793fab945c49daf9032691f8 Mon Sep 17 00:00:00 2001 From: "github-actions[bot]" <41898282+github-actions[bot]@users.noreply.github.com> Date: Tue, 9 Sep 2025 11:30:45 +0100 Subject: [PATCH] chore: sync content to repo (#9071) Co-authored-by: kamranahmedse <4921183+kamranahmedse@users.noreply.github.com> --- .../content/ab-testing@qKlo90-Cy8t_off5Qv8-6.md | 10 +++++++++- .../accesibility@BiyrAHB34evej_0cnDzOa.md | 4 +++- .../accessibility@wtEzdO_ZNu9jHJrFS3CrG.md | 9 ++++++++- .../content/accuracy@M1H3Fh09v8udCJIPSJPic.md | 4 +++- .../advanced-queries@-gbb16Wl--Rjx5aoM0krL.md | 9 ++++++++- .../content/airflow@qnUHw2f2VmTPU3-NMnoLl.md | 11 ++++++++++- .../algorithmic-bias@_uLtsnyNNNRcz5A29Zpjl.md | 9 ++++++++- ...log-vs-digital-data@kb216tShKrRPWv7mE9sVa.md | 8 +++++++- .../content/apis@xQDGmVwUkrmGdviOdG8Hu.md | 4 +++- .../content/barplot@BUizLtQ7vpdyBRjS8KyIl.md | 4 +++- ...ic-machine-learning@ZGazuCNruu09bd7C-aSFC.md | 10 +++++++++- 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.../content/what-is-bi@jVXwlHRGgVpcoWCYzSB5W.md | 8 +++++++- .../what-is-data@g5j_mbjx2yZUIK5lfN3eT.md | 4 +++- .../why-bi-matters@NX-YaB_FVjoHYsR6z9QIL.md | 6 +++++- .../window-functions@1toMuRZResgse1AtwEck6.md | 10 +++++++++- ...executive-summaries@Slg3fXGPTa-Z4sdZY86XK.md | 8 +++++++- .../content/xml@ytgK7van84j5DsfD0JyZ3.md | 8 +++++++- 201 files changed, 1391 insertions(+), 202 deletions(-) diff --git a/src/data/roadmaps/bi-analyst/content/ab-testing@qKlo90-Cy8t_off5Qv8-6.md b/src/data/roadmaps/bi-analyst/content/ab-testing@qKlo90-Cy8t_off5Qv8-6.md index acb816a89..7c95340cb 100644 --- a/src/data/roadmaps/bi-analyst/content/ab-testing@qKlo90-Cy8t_off5Qv8-6.md +++ b/src/data/roadmaps/bi-analyst/content/ab-testing@qKlo90-Cy8t_off5Qv8-6.md @@ -1 +1,9 @@ -# A/B Testing \ No newline at end of file +# A/B Testing + +A/B testing, also known as split testing, is a method of comparing two versions of something to determine which one performs better. This is done by showing the two versions (A and B) to similar audiences and measuring which version achieves a specific goal, such as a higher click-through rate or conversion rate. The version that performs better is then implemented. + +Visit the following resources to learn more: + +- [@article@A/B Testing](https://en.wikipedia.org/wiki/A/B_testing) +- [@article@A Refresher on A/B Testing](https://hbr.org/2017/06/a-refresher-on-ab-testing) +- [@video@How to Do A/B Testing: 15 Steps for the Perfect Split Test](https://www.youtube.com/watch?v=vV3g5VuSrIQ) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/accesibility@BiyrAHB34evej_0cnDzOa.md b/src/data/roadmaps/bi-analyst/content/accesibility@BiyrAHB34evej_0cnDzOa.md index 80e24ad92..534c1cf0a 100644 --- a/src/data/roadmaps/bi-analyst/content/accesibility@BiyrAHB34evej_0cnDzOa.md +++ b/src/data/roadmaps/bi-analyst/content/accesibility@BiyrAHB34evej_0cnDzOa.md @@ -1 +1,3 @@ -# Accesibility \ No newline at end of file +# Data Accessibility + +Data accessibility refers to the ease with which individuals or systems can locate, retrieve, and utilize data. It encompasses factors like data discoverability, format compatibility, and the presence of appropriate permissions and tools. Ensuring data is accessible is crucial for effective analysis, reporting, and decision-making, as it allows users to readily leverage available information. \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/accessibility@wtEzdO_ZNu9jHJrFS3CrG.md b/src/data/roadmaps/bi-analyst/content/accessibility@wtEzdO_ZNu9jHJrFS3CrG.md index 55ffef6e3..5e2c02f6a 100644 --- a/src/data/roadmaps/bi-analyst/content/accessibility@wtEzdO_ZNu9jHJrFS3CrG.md +++ b/src/data/roadmaps/bi-analyst/content/accessibility@wtEzdO_ZNu9jHJrFS3CrG.md @@ -1 +1,8 @@ -# Accessibility \ No newline at end of file +# Accessibility in Data Visualization + +Accessibility in data visualization focuses on designing charts and graphs that are usable by everyone, including people with disabilities. This involves considering factors like color contrast, alternative text for screen readers, keyboard navigation, and clear data labels to ensure that the information presented is understandable and interpretable regardless of a user's abilities or assistive technology. + +Visit the following resources to learn more: + +- [@article@10 Guidelines for DataViz Accessibility](https://www.highcharts.com/blog/tutorials/10-guidelines-for-dataviz-accessibility/) +- [@video@Accessibility in Data Visualisation](https://www.youtube.com/watch?v=OOPeS_xWoKQ) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/accuracy@M1H3Fh09v8udCJIPSJPic.md b/src/data/roadmaps/bi-analyst/content/accuracy@M1H3Fh09v8udCJIPSJPic.md index 1de9e8fb1..5f7e90d1b 100644 --- a/src/data/roadmaps/bi-analyst/content/accuracy@M1H3Fh09v8udCJIPSJPic.md +++ b/src/data/roadmaps/bi-analyst/content/accuracy@M1H3Fh09v8udCJIPSJPic.md @@ -1 +1,3 @@ -# Accuracy \ No newline at end of file +# Accuracy + +Accuracy refers to the degree to which data correctly reflects the real-world object or event it is intended to represent. It ensures that the data values are correct, reliable, and free from errors, misrepresentations, or inconsistencies. High accuracy is crucial for making sound business decisions and generating trustworthy insights. \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/advanced-queries@-gbb16Wl--Rjx5aoM0krL.md b/src/data/roadmaps/bi-analyst/content/advanced-queries@-gbb16Wl--Rjx5aoM0krL.md index 19b267f22..beefcb988 100644 --- a/src/data/roadmaps/bi-analyst/content/advanced-queries@-gbb16Wl--Rjx5aoM0krL.md +++ b/src/data/roadmaps/bi-analyst/content/advanced-queries@-gbb16Wl--Rjx5aoM0krL.md @@ -1 +1,8 @@ -# Advanced Queries \ No newline at end of file +# Advanced SQL Queries + +Advanced SQL queries go beyond basic data retrieval and manipulation. They involve using more complex techniques like subqueries, window functions, common table expressions (CTEs), and stored procedures to analyze data in greater depth. These techniques allow you to perform sophisticated calculations, compare rows, and organize data for more meaningful insights. + +Visit the following resources to learn more: + +- [@article@25 Advanced SQL Query Examples](https://learnsql.com/blog/25-advanced-sql-query-examples/) +- [@official@SQL Roadmap](https://roadmap.sh/sql) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/airflow@qnUHw2f2VmTPU3-NMnoLl.md b/src/data/roadmaps/bi-analyst/content/airflow@qnUHw2f2VmTPU3-NMnoLl.md index f8ca3ee6d..337548e38 100644 --- a/src/data/roadmaps/bi-analyst/content/airflow@qnUHw2f2VmTPU3-NMnoLl.md +++ b/src/data/roadmaps/bi-analyst/content/airflow@qnUHw2f2VmTPU3-NMnoLl.md @@ -1 +1,10 @@ -# Airflow \ No newline at end of file +# Airflow + +Airflow is a platform to programmatically author, schedule and monitor workflows. Use airflow to author workflows as directed acyclic graphs (DAGs) of tasks. The airflow scheduler executes your tasks on an array of workers while following the specified dependencies. Rich command line utilities make performing complex surgeries on DAGs a snap. The rich user interface makes it easy to visualize pipelines running in production, monitor progress, and troubleshoot issues when needed. When workflows are defined as code, they become more maintainable, versionable, testable, and collaborative. + +Visit the following resources to learn more: + +- [@official@Airflow](https://airflow.apache.org/) +- [@official@Airflow Documentation](https://airflow.apache.org/docs) +- [@feed@Explore top posts about Apache Airflow](https://app.daily.dev/tags/apache-airflow?ref=roadmapsh) +- [@video@Apache Airflow Tutorial for Data Engineers](https://www.youtube.com/watch?v=y5rYZLBZ_Fw) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/algorithmic-bias@_uLtsnyNNNRcz5A29Zpjl.md b/src/data/roadmaps/bi-analyst/content/algorithmic-bias@_uLtsnyNNNRcz5A29Zpjl.md index 342b5e848..b7cdeb627 100644 --- a/src/data/roadmaps/bi-analyst/content/algorithmic-bias@_uLtsnyNNNRcz5A29Zpjl.md +++ b/src/data/roadmaps/bi-analyst/content/algorithmic-bias@_uLtsnyNNNRcz5A29Zpjl.md @@ -1 +1,8 @@ -# Algorithmic Bias \ No newline at end of file +# Algorithmic Bias + +Algorithmic bias occurs when a computer system reflects the implicit values of the humans who created the algorithm or the data used to train it. This can lead to unfair or discriminatory outcomes for certain groups of people, even if the algorithm is not explicitly designed to be biased. It arises from flawed assumptions, incomplete data, or biased data used in the development process, ultimately perpetuating and amplifying existing societal biases. + +Visit the following resources to learn more: + +- [@article@What Is Algorithmic Bias?](https://www.ibm.com/think/topics/algorithmic-bias) +- [@video@AI: Training Data & Bias](https://www.youtube.com/watch?v=x2mRoFNm22g) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/analog-vs-digital-data@kb216tShKrRPWv7mE9sVa.md b/src/data/roadmaps/bi-analyst/content/analog-vs-digital-data@kb216tShKrRPWv7mE9sVa.md index ea7a094bc..d17720c7b 100644 --- a/src/data/roadmaps/bi-analyst/content/analog-vs-digital-data@kb216tShKrRPWv7mE9sVa.md +++ b/src/data/roadmaps/bi-analyst/content/analog-vs-digital-data@kb216tShKrRPWv7mE9sVa.md @@ -1 +1,7 @@ -# Analog vs Digital Data \ No newline at end of file +# Analog vs. Digital Data + +Analog data is continuous information represented by physical quantities, like sound waves or temperature, that vary smoothly over time. Digital data, on the other hand, is discrete information represented by numerical values, typically binary digits (0s and 1s), allowing for precise storage and manipulation by computers. + +Visit the following resources to learn more: + +- [@article@Analog vs. Digital](https://www.diffen.com/difference/Analog_vs_Digital) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/apis@xQDGmVwUkrmGdviOdG8Hu.md b/src/data/roadmaps/bi-analyst/content/apis@xQDGmVwUkrmGdviOdG8Hu.md index 51117e98c..402fc7ea7 100644 --- a/src/data/roadmaps/bi-analyst/content/apis@xQDGmVwUkrmGdviOdG8Hu.md +++ b/src/data/roadmaps/bi-analyst/content/apis@xQDGmVwUkrmGdviOdG8Hu.md @@ -1 +1,3 @@ -# APIs \ No newline at end of file +# APIs as Data Sources + +APIs (Application Programming Interfaces) are sets of rules and specifications that software programs can follow to communicate with each other. In essence, they allow different applications to exchange data and functionality. As data sources, APIs provide a structured way to access information from various online services, databases, and applications, enabling BI analysts to integrate real-time or near real-time data into their analyses and reports. \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/barplot@BUizLtQ7vpdyBRjS8KyIl.md b/src/data/roadmaps/bi-analyst/content/barplot@BUizLtQ7vpdyBRjS8KyIl.md index ab8d35a26..cfb90248d 100644 --- a/src/data/roadmaps/bi-analyst/content/barplot@BUizLtQ7vpdyBRjS8KyIl.md +++ b/src/data/roadmaps/bi-analyst/content/barplot@BUizLtQ7vpdyBRjS8KyIl.md @@ -1 +1,3 @@ -# Barplot \ No newline at end of file +# Barplots + +A barplot, also known as a bar chart or bar graph, is a visual representation of data that uses rectangular bars to compare different categories or groups. The length or height of each bar corresponds to the value it represents, allowing for easy comparison of quantities across different categories. Barplots can be oriented vertically (column charts) or horizontally (bar charts), and are commonly used to display frequencies, averages, or other summary statistics. \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/basic-machine-learning@ZGazuCNruu09bd7C-aSFC.md b/src/data/roadmaps/bi-analyst/content/basic-machine-learning@ZGazuCNruu09bd7C-aSFC.md index b0689d728..3137a0e24 100644 --- a/src/data/roadmaps/bi-analyst/content/basic-machine-learning@ZGazuCNruu09bd7C-aSFC.md +++ b/src/data/roadmaps/bi-analyst/content/basic-machine-learning@ZGazuCNruu09bd7C-aSFC.md @@ -1 +1,9 @@ -# Basic Machine Learning \ No newline at end of file +# Basic Machine Learning + +Machine learning fundamentals encompass the key concepts and techniques that enable systems to learn from data and make predictions or decisions without being explicitly programmed. At its core, machine learning involves algorithms that can identify patterns in data and improve over time with experience. Key areas include supervised learning (where models are trained on labeled data), unsupervised learning (where models identify patterns in unlabeled data), and reinforcement learning (where agents learn to make decisions based on feedback from their actions). Essential components also include data preprocessing, feature selection, model training, evaluation metrics, and the importance of avoiding overfitting. Understanding these fundamentals is crucial for developing effective machine learning applications across various domains. + +Visit the following resources to learn more: + +- [@article@What Is Machine Learning (ML)?](https://www.ibm.com/think/topics/machine-learning) +- [@course@Fundamentals of Machine Learning - Microsoft](https://learn.microsoft.com/en-us/training/modules/fundamentals-machine-learning/) +- [@course@MLCourse.ai](https://mlcourse.ai/) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/basic-queries@TuBJ2yUz1c5KMRGVHdvU5.md b/src/data/roadmaps/bi-analyst/content/basic-queries@TuBJ2yUz1c5KMRGVHdvU5.md index f6b6c5a9d..45df6b0df 100644 --- a/src/data/roadmaps/bi-analyst/content/basic-queries@TuBJ2yUz1c5KMRGVHdvU5.md +++ b/src/data/roadmaps/bi-analyst/content/basic-queries@TuBJ2yUz1c5KMRGVHdvU5.md @@ -1 +1,9 @@ -# Basic Queries \ No newline at end of file +# Basic Queries + +Learning how to make basic SQL queries in esencial for BI analysts. Queries are the foundation for retrieving data from a SQL database. They involve using the `SELECT` statement to specify which columns to retrieve, the `FROM` clause to indicate the table to retrieve data from, and optionally, the `WHERE` clause to filter the data based on specific conditions. These queries allow you to extract specific information from a database, forming the basis for more complex data analysis and reporting. + +Visit the following resources to learn more: + +- [@article@SQL Basics Cheat Sheet](https://www.datacamp.com/cheat-sheet/sql-basics-cheat-sheet?utm_cid=19589720821&utm_aid=152984012854&utm_campaign=230119_1-ps-other~dsa~tofu_2-b2c_3-emea_4-prc_5-na_6-na_7-le_8-pdsh-go_9-nb-e_10-na_11-na&utm_loc=20296-&utm_mtd=-c&utm_kw=&utm_source=google&utm_medium=paid_search&utm_content=ps-other~emea-en~dsa~tofu~cheat-sheet-sql&gad_source=1&gad_campaignid=19589720821&gbraid=0AAAAADQ9WsHi-NrpYc5jD1jwOcO6JW2ib&gclid=CjwKCAjwk7DFBhBAEiwAeYbJsaTs85KOpxx2r27-znQYfeTOvKItMJ2YK6xamy5KiqyFRewGTE-AzRoCLXwQAvD_BwE) +- [@article@Basic SQL Commands](https://www.freecodecamp.org/news/basic-sql-commands/) +- [@official@SQL Roadmap](https://roadmap.sh/sql) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/beyond-linear-regression@_QyIZ2_vH3e3yic5NTuak.md b/src/data/roadmaps/bi-analyst/content/beyond-linear-regression@_QyIZ2_vH3e3yic5NTuak.md index 72d9077d1..05339f21d 100644 --- a/src/data/roadmaps/bi-analyst/content/beyond-linear-regression@_QyIZ2_vH3e3yic5NTuak.md +++ b/src/data/roadmaps/bi-analyst/content/beyond-linear-regression@_QyIZ2_vH3e3yic5NTuak.md @@ -1 +1,9 @@ -# Beyond Linear Regression \ No newline at end of file +# Beyond Linear Regression + + While linear regressions are widely popular in predictive modelling, they don't always work. Fortunately, there's a wide array of statistical methods that can be to model relationships between variables when the assumption of a linear relationship is not appropriate. These techniques, such as polynomial, exponential, logarithmic, and logistic regression allow for capturing more complex and non-linear patterns in data, leading to more accurate predictions and insights. They are essential when the relationship between the independent and dependent variables curves or changes direction. + +Visit the following resources to learn more: + +- [@article@Nonlinear regression](https://en.wikipedia.org/wiki/Nonlinear_regression) +- [@video@Nonlinear regression - the basics](https://www.youtube.com/watch?v=4hYGiG4qVf4) +- [@course@Intro to Inferential Statistics](https://www.udacity.com/course/intro-to-inferential-statistics--ud201) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/bi-analyst-vs-other-roles@JFNCITtE1YtcYmLfGfF5T.md b/src/data/roadmaps/bi-analyst/content/bi-analyst-vs-other-roles@JFNCITtE1YtcYmLfGfF5T.md index ff76f642d..bdb3d94a4 100644 --- a/src/data/roadmaps/bi-analyst/content/bi-analyst-vs-other-roles@JFNCITtE1YtcYmLfGfF5T.md +++ b/src/data/roadmaps/bi-analyst/content/bi-analyst-vs-other-roles@JFNCITtE1YtcYmLfGfF5T.md @@ -1,3 +1,7 @@ # BI Analyst vs. Other Roles -A BI Analyst focuses on analyzing data to provide insights and recommendations for business improvements. This role differs from other data-related roles like Data Scientists, who build predictive models, or Data Engineers, who focus on building and maintaining data infrastructure. While a BI Analyst uses data to understand past and current performance, other roles might focus on predicting future outcomes or ensuring the data is readily available for analysis. \ No newline at end of file +A BI Analyst focuses on analyzing data (normally, structured data stored in a data warehouse) and leverage it to create insights and recommendations for business improvements. This role differs from other data-related roles like **Data Scientists**, who build predictive models, or **Data Engineers**, who focus on building and maintaining data infrastructure. While a BI Analyst uses data to understand past and current performance, other roles might focus on predicting future outcomes or ensuring the data is readily available for analysis. + +Visit the following resources to learn more: + +- [@article@The Types of Data Science Roles Explained](https://365datascience.com/career-advice/types-of-data-science-roles-explained/) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/bi-communities@X8U-NQD0rYqFr_xgDWL2s.md b/src/data/roadmaps/bi-analyst/content/bi-communities@X8U-NQD0rYqFr_xgDWL2s.md index 9aa58f0ad..b8e68625f 100644 --- a/src/data/roadmaps/bi-analyst/content/bi-communities@X8U-NQD0rYqFr_xgDWL2s.md +++ b/src/data/roadmaps/bi-analyst/content/bi-communities@X8U-NQD0rYqFr_xgDWL2s.md @@ -1 +1,9 @@ -# BI Communities \ No newline at end of file +# BI Communities + +BI communities are groups of people who share an interest in business intelligence. These communities provide a space for BI professionals to connect, share knowledge, and learn from each other. They often host events, online forums, and other resources to help members grow their skills and advance their careers. Some of the most popular BI communities include the Data Visualization Society, the Tableau Community, and the Power BI Forums. + +Visit the following resources to learn more: + +- [@article@Tableau Community](https://community.tableau.com/s/) +- [@article@Power Bi Forums](https://community.fabric.microsoft.com/t5/Power-BI-forums/ct-p/powerbi) +- [@article@Data Visualization Society](https://www.datavisualizationsociety.org/) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/bi-competitions@aTGsJj7Ntv5BWIzjaqvu_.md b/src/data/roadmaps/bi-analyst/content/bi-competitions@aTGsJj7Ntv5BWIzjaqvu_.md index e28a86815..7efdb0cbf 100644 --- a/src/data/roadmaps/bi-analyst/content/bi-competitions@aTGsJj7Ntv5BWIzjaqvu_.md +++ b/src/data/roadmaps/bi-analyst/content/bi-competitions@aTGsJj7Ntv5BWIzjaqvu_.md @@ -1 +1,8 @@ -# BI Competitions \ No newline at end of file +# BI Competitions + +BI competitions are events where individuals or teams use data analysis and visualization skills to solve business problems. Participants analyze datasets, build dashboards, and present insights to judges. These competitions offer a chance to showcase skills, learn new techniques, and gain recognition in the field. Popular examples include the Microsoft Fabric Community Conference Hackathon, Kaggle competitions focused on business intelligence, and the Data Visualization Society's challenges. + +Visit the following resources to learn more: + +- [@article@Kaggle Competitions](https://www.kaggle.com/competitions) +- [@article@Microsoft Fabric & AI Learning Hackathon](https://developer.microsoft.com/en-us/reactor/series/s-1393/) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/bi-platforms@kpRqKLtAd3IO3nbs8Yxrh.md b/src/data/roadmaps/bi-analyst/content/bi-platforms@kpRqKLtAd3IO3nbs8Yxrh.md index e9ec619cd..208d31681 100644 --- a/src/data/roadmaps/bi-analyst/content/bi-platforms@kpRqKLtAd3IO3nbs8Yxrh.md +++ b/src/data/roadmaps/bi-analyst/content/bi-platforms@kpRqKLtAd3IO3nbs8Yxrh.md @@ -1 +1,7 @@ -# BI Platforms \ No newline at end of file +# BI Platforms + +BI Platforms are software systems that provide a range of tools and capabilities for business intelligence, including data integration, data analysis, reporting, dashboarding, and data visualization. They enable users to access, analyze, and share insights from data to support better decision-making across an organization. These platforms often support various data sources and offer features for collaboration and data governance. + +Visit the following resources to learn more: + +- [@article@Analytics and Business Intelligence Platforms Reviews and Ratings](https://www.gartner.com/reviews/market/analytics-business-intelligence-platforms) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/bias-recognition@9aNVqEyygNGeicdce5X8b.md b/src/data/roadmaps/bi-analyst/content/bias-recognition@9aNVqEyygNGeicdce5X8b.md index 622b04526..684edda40 100644 --- a/src/data/roadmaps/bi-analyst/content/bias-recognition@9aNVqEyygNGeicdce5X8b.md +++ b/src/data/roadmaps/bi-analyst/content/bias-recognition@9aNVqEyygNGeicdce5X8b.md @@ -1 +1,7 @@ -# Bias Recognition \ No newline at end of file +# Bias Recognition + +Bias recognition involves identifying and understanding systematic errors in data or analysis that can lead to unfair or inaccurate conclusions. These biases can arise from various sources, including data collection methods, sampling techniques, or even the assumptions made during analysis. Recognizing these biases is crucial for ensuring that data-driven insights are reliable and equitable. + +Visit the following resources to learn more: + +- [@article@What is Data Bias?](https://www.ibm.com/think/topics/data-bias) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/building-your-portfolio@UIdwl_KLELI8xL2VxYJmX.md b/src/data/roadmaps/bi-analyst/content/building-your-portfolio@UIdwl_KLELI8xL2VxYJmX.md index c42b2d007..4b04ddc6a 100644 --- a/src/data/roadmaps/bi-analyst/content/building-your-portfolio@UIdwl_KLELI8xL2VxYJmX.md +++ b/src/data/roadmaps/bi-analyst/content/building-your-portfolio@UIdwl_KLELI8xL2VxYJmX.md @@ -1 +1,7 @@ -# Building Your Portfolio \ No newline at end of file +# Building Your Portfolio + +A portfolio showcases your BI skills and experience to potential employers. It's a collection of projects, visualizations, and analyses that demonstrate your ability to solve business problems using data. A strong portfolio highlights your technical proficiency, analytical thinking, and communication skills, giving tangible evidence of your capabilities beyond a resume. + +Visit the following resources to learn more: + +- [@article@How to Build a Data Analyst Portfolio: Tips for Success](https://www.coursera.org/articles/how-to-build-a-data-analyst-portfolio) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/business-acumen@OmhvVSTtzH5sxOIZRVYfQ.md b/src/data/roadmaps/bi-analyst/content/business-acumen@OmhvVSTtzH5sxOIZRVYfQ.md index eddfecc2a..26b88cc34 100644 --- a/src/data/roadmaps/bi-analyst/content/business-acumen@OmhvVSTtzH5sxOIZRVYfQ.md +++ b/src/data/roadmaps/bi-analyst/content/business-acumen@OmhvVSTtzH5sxOIZRVYfQ.md @@ -1 +1,8 @@ -# Business Acumen \ No newline at end of file +# Business Acumen + +Business acumen is the ability to quickly understand how a business operates and makes money. It involves grasping the key financial drivers, competitive landscape, and strategic priorities of an organization. This understanding allows individuals to make informed decisions and contribute effectively to achieving business goals. + +Visit the following resources to learn more: + +- [@article@Business acumen](https://en.wikipedia.org/wiki/Business_acumen) +- [@video@Business Acumen 101](https://www.youtube.com/watch?v=JwhPhS26Mos) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/calculated-fields--measures@fFzCnLfZ_vSbhQjdAKLlJ.md b/src/data/roadmaps/bi-analyst/content/calculated-fields--measures@fFzCnLfZ_vSbhQjdAKLlJ.md index de3d89201..d55e8de9f 100644 --- a/src/data/roadmaps/bi-analyst/content/calculated-fields--measures@fFzCnLfZ_vSbhQjdAKLlJ.md +++ b/src/data/roadmaps/bi-analyst/content/calculated-fields--measures@fFzCnLfZ_vSbhQjdAKLlJ.md @@ -1 +1,3 @@ -# Calculated Fields & Measures \ No newline at end of file +# Calculated Fields & Measures + +Calculated fields and measures are custom computations derived from existing data within a data model. They allow you to create new insights and metrics by applying formulas, functions, and logic to raw data. These calculations can involve aggregations, arithmetic operations, conditional statements, and more, enabling you to analyze data in ways not directly available from the original dataset. Modern BI tools usually come with capabilities to create custom calculated fields and measures. \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/categorical-vs-numerical@yXz6MkU3-HnlkmRmYh-Ev.md b/src/data/roadmaps/bi-analyst/content/categorical-vs-numerical@yXz6MkU3-HnlkmRmYh-Ev.md index 8fcb5c021..b86b03fe7 100644 --- a/src/data/roadmaps/bi-analyst/content/categorical-vs-numerical@yXz6MkU3-HnlkmRmYh-Ev.md +++ b/src/data/roadmaps/bi-analyst/content/categorical-vs-numerical@yXz6MkU3-HnlkmRmYh-Ev.md @@ -1 +1,7 @@ -# Categorical vs Numerical \ No newline at end of file +# Categorical vs Numerical + +Categorical data describes groups or qualities and uses words or labels (e.g., hair color), while numerical data represents measurable quantities with numbers (e.g., height). Numerical data can be discrete (countable, like the number of books) or continuous (measurable within a range, like temperature), whereas categorical data can be nominal (unordered categories, like gender) or ordinal (ordered categories, like shirt sizes). + +Visit the following resources to learn more: + +- [@article@Intro to Statistics](https://www.udacity.com/course/intro-to-statistics--st101) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/ccpa@IwnXDA-f3FHK4EEeFuToC.md b/src/data/roadmaps/bi-analyst/content/ccpa@IwnXDA-f3FHK4EEeFuToC.md index f59acc608..524f02fd3 100644 --- a/src/data/roadmaps/bi-analyst/content/ccpa@IwnXDA-f3FHK4EEeFuToC.md +++ b/src/data/roadmaps/bi-analyst/content/ccpa@IwnXDA-f3FHK4EEeFuToC.md @@ -1 +1,8 @@ -# CCPA \ No newline at end of file +# CCPA + +The California Consumer Privacy Act (CCPA) is a California state law that grants consumers specific rights regarding their personal information held by businesses. These rights include the right to know what personal information is being collected about them, the right to request deletion of their personal information, and the right to opt-out of the sale of their personal information. CCPA aims to give consumers more control over their data and increase transparency in data handling practices. + +Visit the following resources to learn more: + +- [@official@California Consumer Privacy Act (CCPA)](https://oag.ca.gov/privacy/ccpa) +- [@article@What is the CCPA?](https://www.cloudflare.com/en-gb/learning/privacy/what-is-the-ccpa/) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/central-tendency@F-fC2JWOuEeDbOHH1O6EB.md b/src/data/roadmaps/bi-analyst/content/central-tendency@F-fC2JWOuEeDbOHH1O6EB.md index 697568987..34ad6bd8d 100644 --- a/src/data/roadmaps/bi-analyst/content/central-tendency@F-fC2JWOuEeDbOHH1O6EB.md +++ b/src/data/roadmaps/bi-analyst/content/central-tendency@F-fC2JWOuEeDbOHH1O6EB.md @@ -1 +1,7 @@ -# Central Tendency \ No newline at end of file +# Central Tendency + +Measures of central tendency focus on the average or middle values of datasets. They aim to provide a summary of the entire dataset with one representative number.The most common measures of central tendency are the arithmetic mean, the median, and the mode. A middle tendency can be calculated for either a finite set of values or for a theoretical distribution, such as the normal distribution. + +Visit the following resources to learn more: + +- [@article@Central tendency](https://en.wikipedia.org/wiki/Central_tendency) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/certifications@hqpFbDhAvyT9_4hcoSLhC.md b/src/data/roadmaps/bi-analyst/content/certifications@hqpFbDhAvyT9_4hcoSLhC.md index 208afdd72..d0da3b964 100644 --- a/src/data/roadmaps/bi-analyst/content/certifications@hqpFbDhAvyT9_4hcoSLhC.md +++ b/src/data/roadmaps/bi-analyst/content/certifications@hqpFbDhAvyT9_4hcoSLhC.md @@ -1 +1,8 @@ -# Certifications \ No newline at end of file +# Certifications for BI Analysts + +Certifications for BI Analysts are credentials that validate a professional's skills and knowledge in business intelligence tools, techniques, and methodologies. These certifications often cover areas like data analysis, data visualization, data warehousing, and specific software platforms such as Tableau, Power BI, or SQL. Earning a certification can demonstrate expertise to employers and clients, potentially leading to career advancement and increased earning potential. + +Visit the following resources to learn more: + +- [@article@16 Top Business Intelligence Certifications for a Successful Career](https://onlinedegrees.sandiego.edu/business-intelligence-certifications/) +- [@article@9 Popular Data Analyst Certifications 2025 Guide](https://www.onlc.com/blog/popular-data-analyst-certifications/) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/change-management@vDQF2oaybSewNu3EMs6zG.md b/src/data/roadmaps/bi-analyst/content/change-management@vDQF2oaybSewNu3EMs6zG.md index 9a20f5d37..9a900a39d 100644 --- a/src/data/roadmaps/bi-analyst/content/change-management@vDQF2oaybSewNu3EMs6zG.md +++ b/src/data/roadmaps/bi-analyst/content/change-management@vDQF2oaybSewNu3EMs6zG.md @@ -1 +1,3 @@ -# Change Management \ No newline at end of file +# Change Management + +Change management is the process, tools, and techniques used to manage the people-side of change to achieve the required business outcome. It involves helping individuals and teams understand, accept, and adapt to changes in their work environment, processes, technologies, or organizational structure. Effective change management minimizes disruption, resistance, and negative impacts, while maximizing adoption and realizing the benefits of the change initiative. \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/chart-categories@GVgfPajmSqIgFZ6u2I1tK.md b/src/data/roadmaps/bi-analyst/content/chart-categories@GVgfPajmSqIgFZ6u2I1tK.md index 78557e97a..5581681f6 100644 --- a/src/data/roadmaps/bi-analyst/content/chart-categories@GVgfPajmSqIgFZ6u2I1tK.md +++ b/src/data/roadmaps/bi-analyst/content/chart-categories@GVgfPajmSqIgFZ6u2I1tK.md @@ -1 +1,8 @@ -# Chart Categories \ No newline at end of file +# Chart Categories + +Charts are visual representations of data, used to identify patterns, trends, and relationships. They generally fall into a few main categories: **comparison** charts (like bar charts and column charts) which show differences between values; **relationship** charts (such as scatter plots) that reveal correlations between variables; **composition** charts (like pie charts and stacked area charts) which display parts of a whole; and **distribution** charts (histograms and box plots) that illustrate the spread and frequency of data. Choosing the right chart type depends on the data you have and the story you want to tell. + +Visit the following resources to learn more: + +- [@article@The Python Graph Gallery](https://python-graph-gallery.com/) +- [@article@The Data Visualisation Catalogue](https://datavizcatalogue.com/) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/cloud-bi-ecosystem@zGU6DyEm6xEYf1_73cbjL.md b/src/data/roadmaps/bi-analyst/content/cloud-bi-ecosystem@zGU6DyEm6xEYf1_73cbjL.md index 95232d714..f914ec234 100644 --- a/src/data/roadmaps/bi-analyst/content/cloud-bi-ecosystem@zGU6DyEm6xEYf1_73cbjL.md +++ b/src/data/roadmaps/bi-analyst/content/cloud-bi-ecosystem@zGU6DyEm6xEYf1_73cbjL.md @@ -1 +1,3 @@ -# Cloud BI Ecosystem \ No newline at end of file +# Cloud BI Ecosystem + +A Cloud BI Ecosystem refers to the collection of cloud-based services, tools, and technologies that work together to enable business intelligence (BI) and analytics. This ecosystem typically includes data storage, data integration, data processing, data visualization, and reporting capabilities, all hosted and managed in the cloud. It allows organizations to leverage the scalability, flexibility, and cost-effectiveness of the cloud to gain insights from their data. \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/cloud-computing-basics@_KYKLd-RNhVy-Sn1A-G5j.md b/src/data/roadmaps/bi-analyst/content/cloud-computing-basics@_KYKLd-RNhVy-Sn1A-G5j.md index 4e76f9d97..c6329e09a 100644 --- a/src/data/roadmaps/bi-analyst/content/cloud-computing-basics@_KYKLd-RNhVy-Sn1A-G5j.md +++ b/src/data/roadmaps/bi-analyst/content/cloud-computing-basics@_KYKLd-RNhVy-Sn1A-G5j.md @@ -1 +1,9 @@ -# Cloud Computing Basics \ No newline at end of file +# Cloud Computing + +**Cloud Computing** refers to the delivery of computing services over the internet rather than using local servers or personal devices. These services include servers, storage, databases, networking, software, analytics, and intelligence. Cloud Computing enables faster innovation, flexible resources, and economies of scale. There are various types of cloud computing such as public clouds, private clouds, and hybrids clouds. Furthermore, it's divided into different services like Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS). These services differ mainly in the level of control an organization has over their data and infrastructures. + +Visit the following resources to learn more: + +- [@article@Cloud Computing - IBM](https://www.ibm.com/think/topics/cloud-computing) +- [@article@What is Cloud Computing? - Azure](https://azure.microsoft.com/en-gb/resources/cloud-computing-dictionary/what-is-cloud-computing) +- [@video@hat is Cloud Computing?](https://www.youtube.com/watch?v=mxT233EdY5c) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/cloud-data-warehouses@D94743lQ1fAerVSpJWXfP.md b/src/data/roadmaps/bi-analyst/content/cloud-data-warehouses@D94743lQ1fAerVSpJWXfP.md index 77493d769..5e11c6ac8 100644 --- a/src/data/roadmaps/bi-analyst/content/cloud-data-warehouses@D94743lQ1fAerVSpJWXfP.md +++ b/src/data/roadmaps/bi-analyst/content/cloud-data-warehouses@D94743lQ1fAerVSpJWXfP.md @@ -1 +1,7 @@ -# Cloud data warehouses \ No newline at end of file +# Cloud Data Warehouses + +Cloud data warehouses are databases designed for analytical workloads that are hosted on cloud computing platforms. They allow businesses to store and analyze large volumes of data from various sources in a centralized, scalable, and cost-effective manner. These warehouses are optimized for read-heavy operations, enabling fast query performance for business intelligence and reporting. + +Visit the following resources to learn more: + +- [@article@What is a Data Warehouse?](https://cloud.google.com/learn/what-is-a-data-warehouse) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/cloud@WXk0-vebMUQC25he2lmbh.md b/src/data/roadmaps/bi-analyst/content/cloud@WXk0-vebMUQC25he2lmbh.md index bd82553bb..6dca212b1 100644 --- a/src/data/roadmaps/bi-analyst/content/cloud@WXk0-vebMUQC25he2lmbh.md +++ b/src/data/roadmaps/bi-analyst/content/cloud@WXk0-vebMUQC25he2lmbh.md @@ -1 +1,3 @@ -# Cloud \ No newline at end of file +# Cloud Data Sources + +Cloud data sources refer to data that is stored and accessed through a network of remote servers hosted on the internet, rather than on local servers or personal devices. These sources can include databases, data warehouses, data lakes, and various applications offered by cloud providers like AWS, Azure, and Google Cloud. They offer scalability, accessibility, and often cost-effectiveness for storing and processing large volumes of data. \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/clv@OqHNW0PzIRsw7IBgh5U5Q.md b/src/data/roadmaps/bi-analyst/content/clv@OqHNW0PzIRsw7IBgh5U5Q.md index af7228dde..5a763eb4a 100644 --- a/src/data/roadmaps/bi-analyst/content/clv@OqHNW0PzIRsw7IBgh5U5Q.md +++ b/src/data/roadmaps/bi-analyst/content/clv@OqHNW0PzIRsw7IBgh5U5Q.md @@ -1 +1,7 @@ -# CLV \ No newline at end of file +# Customer Lifetime Value (CLV) + +Customer Lifetime Value (CLV) predicts the total revenue a business can expect from a single customer account throughout their relationship. It considers factors like purchase frequency, average order value, and customer lifespan to estimate the long-term profitability of each customer. This metric helps businesses understand which customer segments are most valuable and informs decisions about customer acquisition, retention, and marketing strategies. + +Visit the following resources to learn more: + +- [@article@What Customer Lifetime Value (CLV) Is and How to Calculate It](https://www.netsuite.com/portal/resource/articles/ecommerce/customer-lifetime-value-clv.shtml) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/coherence@4U66ZrBZqg7-ckOTmxAQj.md b/src/data/roadmaps/bi-analyst/content/coherence@4U66ZrBZqg7-ckOTmxAQj.md index 99e0ec698..0c99b2886 100644 --- a/src/data/roadmaps/bi-analyst/content/coherence@4U66ZrBZqg7-ckOTmxAQj.md +++ b/src/data/roadmaps/bi-analyst/content/coherence@4U66ZrBZqg7-ckOTmxAQj.md @@ -1 +1,3 @@ -# Coherence \ No newline at end of file +# Coherence in Data Quality + +Coherence, within the realm of data quality, refers to the logical consistency and understandability of data across different datasets or within a single dataset. It ensures that data elements relate to each other in a meaningful and expected way, avoiding contradictions and ambiguities. High coherence means the data tells a clear and consistent story, making it reliable for analysis and decision-making. \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/cohort-analysis@R2zg0Ql-RsnIkV5Gmc1vN.md b/src/data/roadmaps/bi-analyst/content/cohort-analysis@R2zg0Ql-RsnIkV5Gmc1vN.md index a9444ea5c..f9b189254 100644 --- a/src/data/roadmaps/bi-analyst/content/cohort-analysis@R2zg0Ql-RsnIkV5Gmc1vN.md +++ b/src/data/roadmaps/bi-analyst/content/cohort-analysis@R2zg0Ql-RsnIkV5Gmc1vN.md @@ -1 +1,8 @@ -# Cohort Analysis \ No newline at end of file +# Cohort Analysis + +Cohort analysis is a behavioral analytics technique that groups users with shared characteristics over a specific time span. These groups, or cohorts, are then tracked and compared to understand how their behavior evolves over time. This helps identify patterns, trends, and insights related to user engagement, retention, and other key metrics. + +Visit the following resources to learn more: + +- [@article@Understanding Cohort Analysis: A Comprehensive Guide 101](https://hevodata.com/learn/understanding-cohort-analysis-a-guide/) +- [@article@Cohort analysis](https://en.wikipedia.org/wiki/Cohort_analysis) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/color-theory@SJGEkoTSPK2ck4IvaK6Gz.md b/src/data/roadmaps/bi-analyst/content/color-theory@SJGEkoTSPK2ck4IvaK6Gz.md index 7c44e50be..8f6a9aa6b 100644 --- a/src/data/roadmaps/bi-analyst/content/color-theory@SJGEkoTSPK2ck4IvaK6Gz.md +++ b/src/data/roadmaps/bi-analyst/content/color-theory@SJGEkoTSPK2ck4IvaK6Gz.md @@ -1 +1,8 @@ -# Color theory \ No newline at end of file +# Color Theory + +Color theory is a set of principles that guide how colors are mixed, combined, and used to create visually appealing and effective designs. It encompasses understanding the color wheel, color harmonies, and the psychological effects of different colors. Applying color theory helps ensure that visualizations are not only aesthetically pleasing but also communicate data accurately and effectively. + +Visit the following resources to learn more: + +- [@article@How to choose colors for data visualizations](https://www.atlassian.com/data/charts/how-to-choose-colors-data-visualization) +- [@video@Why Colors Matter in Data Visualization? What is Color Theory?](https://www.youtube.com/watch?v=Zs-Rbkr9LVI) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/communication--storytelling@TBcLXYtKs7_j_h_m2pAyh.md b/src/data/roadmaps/bi-analyst/content/communication--storytelling@TBcLXYtKs7_j_h_m2pAyh.md index 6fcaae63f..262f534ef 100644 --- a/src/data/roadmaps/bi-analyst/content/communication--storytelling@TBcLXYtKs7_j_h_m2pAyh.md +++ b/src/data/roadmaps/bi-analyst/content/communication--storytelling@TBcLXYtKs7_j_h_m2pAyh.md @@ -1 +1,10 @@ -# Communication & Storytelling \ No newline at end of file +# Communication & Storytelling + +Communication and storytelling involve conveying insights and findings from data analysis in a clear, concise, and engaging manner. It's about transforming complex data into understandable narratives that resonate with the audience, enabling them to grasp the significance of the information and make informed decisions. This includes using visuals, language, and structure to effectively present data-driven insights. + +Visit the following resources to learn more: + +- [@article@What is data storytelling?](http://microsoft.com/en-us/power-platform/products/power-bi/topics/data-storytelling) +- [@article@Data Storytelling: How to Effectively Tell a Story with Data](https://online.hbs.edu/blog/post/data-storytelling) +- [@video@Telling Stories with Data in 3 Steps (Quick Study)](https://www.youtube.com/watch?v=r5_34YnCmMY) +- [@book@Effective Data Storytelling: How to drive change with data, narrative, and visuals](https://dl.nemoudar.com/effective-data-storytelling-how-to-drive-change-with-data-narrative-and-visuals-1nbsped-1119615712-9781119615712_compress.pdf) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/compliance-reporting@j-GXKpMnsVuUUUdRxAXLe.md b/src/data/roadmaps/bi-analyst/content/compliance-reporting@j-GXKpMnsVuUUUdRxAXLe.md index ab80831e3..293864872 100644 --- a/src/data/roadmaps/bi-analyst/content/compliance-reporting@j-GXKpMnsVuUUUdRxAXLe.md +++ b/src/data/roadmaps/bi-analyst/content/compliance-reporting@j-GXKpMnsVuUUUdRxAXLe.md @@ -1 +1,7 @@ -# Compliance Reporting \ No newline at end of file +# Compliance Reporting + +Compliance reporting involves creating reports that demonstrate an organization's adherence to laws, regulations, policies, and industry standards. These reports provide evidence of compliance to regulatory bodies, stakeholders, and internal management, ensuring transparency and accountability. They often include key performance indicators (KPIs), metrics, and data visualizations to highlight compliance status and identify areas for improvement. + +Visit the following resources to learn more: + +- [@article@Streamlining Financial Compliance with AI-Powered BI](https://www.strategysoftware.com/blog/streamlining-financial-compliance-with-ai-powered-bi) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/compliance-reporting@omvGuhou7_63k-Fwcc7Mu.md b/src/data/roadmaps/bi-analyst/content/compliance-reporting@omvGuhou7_63k-Fwcc7Mu.md index ab80831e3..11b32ca7f 100644 --- a/src/data/roadmaps/bi-analyst/content/compliance-reporting@omvGuhou7_63k-Fwcc7Mu.md +++ b/src/data/roadmaps/bi-analyst/content/compliance-reporting@omvGuhou7_63k-Fwcc7Mu.md @@ -1 +1,3 @@ -# Compliance Reporting \ No newline at end of file +# Compliance Reporting in Healthcare + +Compliance reporting in healthcare involves creating reports that demonstrate adherence to regulations and standards set by healthcare organizations. These reports track key performance indicators (KPIs) related to patient safety, data security, financial integrity, and quality of care. They are used to identify areas of non-compliance, mitigate risks, and ensure that healthcare providers meet legal and ethical obligations. \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/conferences--webinars@UDF8wyYT8127wfFHcq37P.md b/src/data/roadmaps/bi-analyst/content/conferences--webinars@UDF8wyYT8127wfFHcq37P.md index d3e594a9d..426fbe633 100644 --- a/src/data/roadmaps/bi-analyst/content/conferences--webinars@UDF8wyYT8127wfFHcq37P.md +++ b/src/data/roadmaps/bi-analyst/content/conferences--webinars@UDF8wyYT8127wfFHcq37P.md @@ -1 +1,10 @@ -# Conferences & Webinars \ No newline at end of file +# BI Conferences and Webinars + +BI conferences and webinars are events where professionals in the business intelligence field gather to learn about the latest trends, technologies, and best practices. These events offer opportunities to network with peers, hear from industry experts, and discover new tools and techniques for data analysis and visualization. + +Here are 4 popular BI conferences: + +* **Gartner Data & Analytics Summit:** A leading conference covering a wide range of data and analytics topics. +* **TDWI Conferences:** Focused on data warehousing, business intelligence, and analytics. +* **Data Council:** A community-powered conference for data scientists, engineers, and analysts. +* **Big Data LDN:** A UK-based event showcasing big data and analytics solutions. \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/confidence-intervals@xgP3zIiSEr9dtYcCQikPb.md b/src/data/roadmaps/bi-analyst/content/confidence-intervals@xgP3zIiSEr9dtYcCQikPb.md index fd4ef727f..387945c76 100644 --- a/src/data/roadmaps/bi-analyst/content/confidence-intervals@xgP3zIiSEr9dtYcCQikPb.md +++ b/src/data/roadmaps/bi-analyst/content/confidence-intervals@xgP3zIiSEr9dtYcCQikPb.md @@ -1 +1,8 @@ -# Confidence Intervals \ No newline at end of file +# Confidence Intervals + +Confidence intervals provide a range of values that are likely to contain the true value of a population parameter, such as a mean or proportion. They are calculated from sample data and are associated with a confidence level, indicating the probability that the interval captures the true parameter. A wider interval suggests more uncertainty, while a narrower interval suggests more precision in estimating the parameter. A 95% confidence interval, for example, means that if the same sampling method were repeated many times, 95% of the calculated intervals would contain the true population parameter. + +Visit the following resources to learn more: + +- [@article@What Is a Confidence Interval and How Do You Calculate It?](https://www.investopedia.com/terms/c/confidenceinterval.asp) +- [@article@Confidence interval](https://en.wikipedia.org/wiki/Confidence_interval) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/correlation-analysis@ASHk2LOjlhwpwpWSRs_Bi.md b/src/data/roadmaps/bi-analyst/content/correlation-analysis@ASHk2LOjlhwpwpWSRs_Bi.md index a08c79671..fd3b890f0 100644 --- a/src/data/roadmaps/bi-analyst/content/correlation-analysis@ASHk2LOjlhwpwpWSRs_Bi.md +++ b/src/data/roadmaps/bi-analyst/content/correlation-analysis@ASHk2LOjlhwpwpWSRs_Bi.md @@ -1 +1,9 @@ -# Correlation Analysis \ No newline at end of file +# Correlation Analysis + +Correlation analysis is a statistical method used to determine the strength and direction of a linear relationship between two variables. It helps to understand how changes in one variable are associated with changes in another, indicating whether they tend to increase or decrease together. The correlation coefficient, typically ranging from -1 to +1, quantifies this relationship, with values closer to -1 or +1 indicating a stronger correlation and 0 indicating no linear relationship. + +Visit the following resources to learn more: + +- [@article@Correlation Analysis](https://datatab.net/tutorial/correlation) +- [@article@Correlation](https://en.wikipedia.org/wiki/Correlation) +- [@course@Intro to Inferential Statistics](https://www.udacity.com/course/intro-to-inferential-statistics--ud201) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/correlation-vs-causation@JXYmXAYuA-zxrkl4PRLQd.md b/src/data/roadmaps/bi-analyst/content/correlation-vs-causation@JXYmXAYuA-zxrkl4PRLQd.md index 4220ae605..91c16016c 100644 --- a/src/data/roadmaps/bi-analyst/content/correlation-vs-causation@JXYmXAYuA-zxrkl4PRLQd.md +++ b/src/data/roadmaps/bi-analyst/content/correlation-vs-causation@JXYmXAYuA-zxrkl4PRLQd.md @@ -1 +1,9 @@ -# Correlation vs Causation \ No newline at end of file +# Correlation vs. Causation + +Correlation describes the degree to which two variables tend to move together, indicating a statistical relationship. Causation, on the other hand, implies that one variable directly influences another, meaning a change in one variable produces a change in the other. While correlation can suggest a possible causal relationship, it does not prove it, as other factors might be involved. Essentially, correlation is about association, while causation is about a direct influence + +Visit the following resources to learn more: + +- [@article@Correlation vs. Causation | Difference, Designs & Examples](https://www.scribbr.com/methodology/correlation-vs-causation/) +- [@article@Correlation does not imply causation](https://en.wikipedia.org/wiki/Correlation_does_not_imply_causation) +- [@course@Intro to Inferential Statistics](http://udacity.com/course/intro-to-inferential-statistics--ud201) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/critical-thinking@NFKiPXrkjRre1yUZc27gl.md b/src/data/roadmaps/bi-analyst/content/critical-thinking@NFKiPXrkjRre1yUZc27gl.md index 8ceeface9..c02d66be0 100644 --- a/src/data/roadmaps/bi-analyst/content/critical-thinking@NFKiPXrkjRre1yUZc27gl.md +++ b/src/data/roadmaps/bi-analyst/content/critical-thinking@NFKiPXrkjRre1yUZc27gl.md @@ -1 +1,3 @@ -# Critical Thinking \ No newline at end of file +# Critical Thinking + +Critical thinking involves analyzing information objectively and forming a reasoned judgment. It's about evaluating evidence, identifying assumptions, and considering different perspectives to arrive at well-supported conclusions. This process helps in problem-solving and decision-making by ensuring that conclusions are logical and based on facts rather than emotions or biases. \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/csv@LcLfC6BiOxJAkk2p424wL.md b/src/data/roadmaps/bi-analyst/content/csv@LcLfC6BiOxJAkk2p424wL.md index fce217423..35ac3c043 100644 --- a/src/data/roadmaps/bi-analyst/content/csv@LcLfC6BiOxJAkk2p424wL.md +++ b/src/data/roadmaps/bi-analyst/content/csv@LcLfC6BiOxJAkk2p424wL.md @@ -1 +1,7 @@ -# CSV \ No newline at end of file +# CSV + +CSV (Comma Separated Values) is a plain text file format used to store tabular data, such as spreadsheets or databases. Each line in a CSV file represents a row of data, and the values within each row are separated by commas. It's a simple and widely supported format for exchanging data between different applications. + +Visit the following resources to learn more: + +- [@article@Comma-Separated Values](https://en.wikipedia.org/wiki/Comma-separated_values) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/dashboard-design@KXhNou5nlekbSTfLYPs_8.md b/src/data/roadmaps/bi-analyst/content/dashboard-design@KXhNou5nlekbSTfLYPs_8.md index 3219523d2..55d46079c 100644 --- a/src/data/roadmaps/bi-analyst/content/dashboard-design@KXhNou5nlekbSTfLYPs_8.md +++ b/src/data/roadmaps/bi-analyst/content/dashboard-design@KXhNou5nlekbSTfLYPs_8.md @@ -1 +1,7 @@ -# Dashboard Design \ No newline at end of file +# Dashboard Design + +Dashboard design involves creating visual displays of data that are easy to understand and interpret. It focuses on arranging key performance indicators (KPIs), charts, and other data visualizations in a way that tells a clear and concise story about the underlying data, enabling users to quickly identify trends, patterns, and insights. Effective dashboard design prioritizes clarity, usability, and relevance to the intended audience. + +Visit the following resources to learn more: + +- [@article@Visual storytelling 101: elevating presentations with data visualization](https://medium.com/@mokkup/8-essential-dashboard-design-principles-for-effective-data-visualization-40653c5fd135) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/dashboard-design@qvPTiDbsY5ol_K-BNLmzk.md b/src/data/roadmaps/bi-analyst/content/dashboard-design@qvPTiDbsY5ol_K-BNLmzk.md index 3219523d2..436c38374 100644 --- a/src/data/roadmaps/bi-analyst/content/dashboard-design@qvPTiDbsY5ol_K-BNLmzk.md +++ b/src/data/roadmaps/bi-analyst/content/dashboard-design@qvPTiDbsY5ol_K-BNLmzk.md @@ -1 +1,7 @@ -# Dashboard Design \ No newline at end of file +# Dashboard Design + +Dashboard design involves creating visual interfaces that present key performance indicators (KPIs) and other important data in an easily understandable format. This process includes selecting appropriate charts and graphs, arranging them logically, and ensuring the overall design is clear, concise, and visually appealing to help users quickly gain insights and make informed decisions. + +Visit the following resources to learn more: + +- [@video@ES Saltar navegación power bi dashboard design project Crear Imagen del avatar POWER BI Tutorial From BEGINNER to Pro Level](https://www.youtube.com/watch?v=0BKlUySopU4) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/data-architectures@Zxuvc9F3bINLTdfbsx_S_.md b/src/data/roadmaps/bi-analyst/content/data-architectures@Zxuvc9F3bINLTdfbsx_S_.md index 2356fdf02..6d77be701 100644 --- a/src/data/roadmaps/bi-analyst/content/data-architectures@Zxuvc9F3bINLTdfbsx_S_.md +++ b/src/data/roadmaps/bi-analyst/content/data-architectures@Zxuvc9F3bINLTdfbsx_S_.md @@ -1 +1,7 @@ -# Data Architectures \ No newline at end of file +# Data Architectures + +Data architecture defines how data is collected, stored, transformed, distributed, and consumed within an organization. It provides a blueprint for managing data assets, ensuring data quality, accessibility, and security. This framework encompasses various components, including databases, data warehouses, data lakes, and data pipelines, working together to support business intelligence and analytics. + +Visit the following resources to learn more: + +- [@article@What Is a Data Architecture?](https://www.ibm.com/think/topics/data-architecture) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/data-cleaning@Vo7LJ_W-DBvxvVrnz33BM.md b/src/data/roadmaps/bi-analyst/content/data-cleaning@Vo7LJ_W-DBvxvVrnz33BM.md index 7d04f3ec3..5ab077628 100644 --- a/src/data/roadmaps/bi-analyst/content/data-cleaning@Vo7LJ_W-DBvxvVrnz33BM.md +++ b/src/data/roadmaps/bi-analyst/content/data-cleaning@Vo7LJ_W-DBvxvVrnz33BM.md @@ -1 +1,7 @@ -# Data Cleaning \ No newline at end of file +# Data Cleaning + +Data cleaning, which is often referred as data cleansing or data scrubbing, is one of the most important and initial steps in the data analysis process. As a BI analyst, the bulk of your work often revolves around understanding, cleaning, and standardizing raw data before analysis. Data cleaning involves identifying, correcting or removing any errors or inconsistencies in datasets in order to improve their quality. The process is crucial because it directly determines the accuracy of the insights you generate - garbage in, garbage out. Even the most sophisticated models and visualizations would not be of much use if they're based on dirty data. + +Visit the following resources to learn more: + +- [@article@Data Cleaning](https://www.tableau.com/learn/articles/what-is-data-cleaning) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/data-formats@GsZWvJPNzN6XLDp2G1db4.md b/src/data/roadmaps/bi-analyst/content/data-formats@GsZWvJPNzN6XLDp2G1db4.md index db4f05214..caa26624d 100644 --- a/src/data/roadmaps/bi-analyst/content/data-formats@GsZWvJPNzN6XLDp2G1db4.md +++ b/src/data/roadmaps/bi-analyst/content/data-formats@GsZWvJPNzN6XLDp2G1db4.md @@ -1 +1,3 @@ -# Data Formats \ No newline at end of file +# Data Formats + +Data formats define the structure in which data is stored and organized. These formats dictate how information is encoded, interpreted, and used by different systems and applications. Common examples include CSV (Comma Separated Values) for tabular data, JSON (JavaScript Object Notation) for structured data, and XML (Extensible Markup Language) for hierarchical data. Understanding data formats is crucial for effectively extracting, transforming, and loading (ETL) data, as well as for ensuring data compatibility and integrity across various platforms. \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/data-lake@iqpVtvoebAaoB_Dj9-gdw.md b/src/data/roadmaps/bi-analyst/content/data-lake@iqpVtvoebAaoB_Dj9-gdw.md index 44eca1724..253783ffa 100644 --- a/src/data/roadmaps/bi-analyst/content/data-lake@iqpVtvoebAaoB_Dj9-gdw.md +++ b/src/data/roadmaps/bi-analyst/content/data-lake@iqpVtvoebAaoB_Dj9-gdw.md @@ -1 +1,9 @@ -# Data Lake \ No newline at end of file +# Data lakes + +**Data Lakes** are large-scale data repository systems that store raw, untransformed data, in various formats, from multiple sources. They're often used for big data and real-time analytics requirements. Data lakes preserve the original data format and schema which can be modified as necessary. + +Visit the following resources to learn more: + +- [@article@Data Lake Definition](https://azure.microsoft.com/en-gb/resources/cloud-computing-dictionary/what-is-a-data-lake) +- [@video@What is a Data Lake?](https://www.youtube.com/watch?v=LxcH6z8TFpI) +- [@video@Data Lake VS Data Warehouse VS Data Marts](https://www.youtube.com/watch?v=w9-WoReNKHk) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/data-lineage@F21ypKzpziLCXkiKG1S5Z.md b/src/data/roadmaps/bi-analyst/content/data-lineage@F21ypKzpziLCXkiKG1S5Z.md index 43522b5cf..92fea9023 100644 --- a/src/data/roadmaps/bi-analyst/content/data-lineage@F21ypKzpziLCXkiKG1S5Z.md +++ b/src/data/roadmaps/bi-analyst/content/data-lineage@F21ypKzpziLCXkiKG1S5Z.md @@ -1 +1,8 @@ -# Data Lineage \ No newline at end of file +# Data Lineage + +Data lineage is the process of understanding and documenting the journey of data, from its origin to its destination. It tracks how data is transformed, moved, and used throughout its lifecycle. This includes identifying the sources of data, the transformations applied to it (e.g., cleaning, aggregation), and the systems and users that access or modify it. + +Visit the following resources to learn more: + +- [@article@What Is Data Lineage?](https://www.ibm.com/think/topics/data-lineage) +- [@article@The Ultimate Guide To Data Lineage](http://montecarlodata.com/blog-data-lineage/) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/data-mart@5x4NfuP6dAgjISlB-esIW.md b/src/data/roadmaps/bi-analyst/content/data-mart@5x4NfuP6dAgjISlB-esIW.md index db3fdb970..9e1c3082e 100644 --- a/src/data/roadmaps/bi-analyst/content/data-mart@5x4NfuP6dAgjISlB-esIW.md +++ b/src/data/roadmaps/bi-analyst/content/data-mart@5x4NfuP6dAgjISlB-esIW.md @@ -1 +1,9 @@ -# Data Mart \ No newline at end of file +# Data Mart + +A data mart is a subset of a data warehouse, focused on a specific business function or department. A data mart is streamlined for quicker querying and a more straightforward setup, catering to the specialized needs of a particular team, or function. Data marts only hold data relevant to a specific department or business unit, enabling quicker access to specific datasets, and simpler management + +Visit the following resources to learn more: + +- [@article@What is a Data Mart?](https://www.ibm.com/think/topics/data-mart) +- [@article@Data Mart vs Data Warehouse: a Detailed Comparison](https://www.datacamp.com/blog/data-mart-vs-data-warehouse) +- [@article@Data Lake VS Data Warehouse VS Data Marts](https://www.youtube.com/watch?v=w9-WoReNKHk) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/data-modeling-for-bi@Dk31XtS7wWRzO31sdsEDo.md b/src/data/roadmaps/bi-analyst/content/data-modeling-for-bi@Dk31XtS7wWRzO31sdsEDo.md index e562efb43..1220a74df 100644 --- a/src/data/roadmaps/bi-analyst/content/data-modeling-for-bi@Dk31XtS7wWRzO31sdsEDo.md +++ b/src/data/roadmaps/bi-analyst/content/data-modeling-for-bi@Dk31XtS7wWRzO31sdsEDo.md @@ -1 +1,8 @@ -# Data Modeling for BI \ No newline at end of file +# Data Modeling for BI + +Data modeling involves structuring and organizing data in a way that's optimized for reporting, analysis, and decision-making. It focuses on creating a simplified and efficient representation of data, often using techniques like star or snowflake schemas, to facilitate quick querying and insightful visualizations. The goal is to transform raw data into a format that's easily understood and readily accessible for BI tools and users. + +Visit the following resources to learn more: + +- [@article@What Is Data Modeling? | IBM](https://www.ibm.com/think/topics/data-modeling) +- [@article@Data Modeling Explained: Techniques, Examples, and Best Practices](https://www.datacamp.com/blog/data-modeling) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/data-pipeline-design@yvSf7sGEd7QiaVoetalHc.md b/src/data/roadmaps/bi-analyst/content/data-pipeline-design@yvSf7sGEd7QiaVoetalHc.md index 3d7f5869e..397015bcb 100644 --- a/src/data/roadmaps/bi-analyst/content/data-pipeline-design@yvSf7sGEd7QiaVoetalHc.md +++ b/src/data/roadmaps/bi-analyst/content/data-pipeline-design@yvSf7sGEd7QiaVoetalHc.md @@ -1 +1,7 @@ -# Data Pipeline Design \ No newline at end of file +# Data Pipeline Design + +Data pipeline design involves creating a structured flow for data, from its initial sources to its final destination for analysis and reporting. This process includes extracting data from various sources, transforming it into a usable format, and loading it into a data warehouse or other storage system. A well-designed data pipeline ensures data quality, reliability, and efficiency, enabling timely and accurate insights. + +Visit the following resources to learn more: + +- [@video@Data Engineering Project: Quickly Build a Complex Data Pipeline](https://www.youtube.com/watch?v=IQxhutCbN7A) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/data-quality@bGCMAgaenZ0t3WeO5joyP.md b/src/data/roadmaps/bi-analyst/content/data-quality@bGCMAgaenZ0t3WeO5joyP.md index eea2ee2ab..a3080bf88 100644 --- a/src/data/roadmaps/bi-analyst/content/data-quality@bGCMAgaenZ0t3WeO5joyP.md +++ b/src/data/roadmaps/bi-analyst/content/data-quality@bGCMAgaenZ0t3WeO5joyP.md @@ -1 +1,7 @@ -# Data Quality \ No newline at end of file +# Data Quality + +Data quality refers to the overall usability and reliability of data. It encompasses various dimensions like accuracy, completeness, consistency, timeliness, validity, and uniqueness. High-quality data is essential for making informed decisions and drawing accurate insights, while poor data quality can lead to flawed analyses and incorrect conclusions. + +Visit the following resources to learn more: + +- [@article@What Is Data Quality?](https://www.ibm.com/think/topics/data-quality) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/data-sources@VUgxDDkoxkOcLxqpTDXzt.md b/src/data/roadmaps/bi-analyst/content/data-sources@VUgxDDkoxkOcLxqpTDXzt.md index eef121fa0..73e604f34 100644 --- a/src/data/roadmaps/bi-analyst/content/data-sources@VUgxDDkoxkOcLxqpTDXzt.md +++ b/src/data/roadmaps/bi-analyst/content/data-sources@VUgxDDkoxkOcLxqpTDXzt.md @@ -1 +1,3 @@ -# Data Sources \ No newline at end of file +# Data Sources + +Data sources are the origins from which data is collected. These sources can be varied, ranging from databases and spreadsheets to web APIs and social media feeds. They provide the raw material that is then processed, analyzed, and transformed into meaningful insights. Understanding the different types of data sources and how to access them is crucial for effective data analysis. \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/data-transformation-techniques@hrkMVMYWCedRxhNd2N9wE.md b/src/data/roadmaps/bi-analyst/content/data-transformation-techniques@hrkMVMYWCedRxhNd2N9wE.md index 3f0deea6e..0a77542c8 100644 --- a/src/data/roadmaps/bi-analyst/content/data-transformation-techniques@hrkMVMYWCedRxhNd2N9wE.md +++ b/src/data/roadmaps/bi-analyst/content/data-transformation-techniques@hrkMVMYWCedRxhNd2N9wE.md @@ -1 +1,16 @@ -# Data Transformation Techniques \ No newline at end of file +# Data Transformation Techniques + +Data transformation techniques involve changing data from one format or structure to another. Common techniques include: + +* **Cleaning:** Handling missing values, correcting errors, and removing duplicates. +* **Filtering:** Selecting specific data based on defined criteria. +* **Aggregation:** Summarizing data (e.g., calculating sums, averages, counts). +* **Joining:** Combining data from multiple sources based on related fields. +* **Pivoting:** Rotating data to change rows into columns or vice versa. +* **Normalization/Standardization:** Scaling numerical data to a specific range. +* **Data Type Conversion:** Changing the data type of a field (e.g., string to integer). + +Visit the following resources to learn more: + +- [@article@Data Transformation](https://www.qlik.com/us/data-management/data-transformation) +- [@video@What is Data Transformation? (Types of Data Transformations and Examples!)](https://www.youtube.com/watch?v=TY0NAPAWR3M) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/data-warehouse@wJiKBbTMLhIzelUtKn7jl.md b/src/data/roadmaps/bi-analyst/content/data-warehouse@wJiKBbTMLhIzelUtKn7jl.md index 1ec8cfcaa..930e93373 100644 --- a/src/data/roadmaps/bi-analyst/content/data-warehouse@wJiKBbTMLhIzelUtKn7jl.md +++ b/src/data/roadmaps/bi-analyst/content/data-warehouse@wJiKBbTMLhIzelUtKn7jl.md @@ -1 +1,9 @@ -# Data Warehouse \ No newline at end of file +# Data Warehouse + +**Data Warehouses** are data storage systems which are designed for analyzing, reporting and integrating with transactional systems. The data in a warehouse is clean, consistent, and often transformed to meet wide-range of business requirements. Hence, data warehouses provide structured data but require more processing and management compared to data lakes. + +Visit the following resources to learn more: + +- [@article@What Is a Data Warehouse?](https://www.oracle.com/database/what-is-a-data-warehouse/) +- [@video@What is a Data Warehouse?](https://www.youtube.com/watch?v=k4tK2ttdSDg) +- [@video@Data Lake VS Data Warehouse VS Data Marts](https://www.youtube.com/watch?v=w9-WoReNKHk) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/databases@g44bQY90HOeI_dZ8gK2Uj.md b/src/data/roadmaps/bi-analyst/content/databases@g44bQY90HOeI_dZ8gK2Uj.md index 602f6d863..0b8634263 100644 --- a/src/data/roadmaps/bi-analyst/content/databases@g44bQY90HOeI_dZ8gK2Uj.md +++ b/src/data/roadmaps/bi-analyst/content/databases@g44bQY90HOeI_dZ8gK2Uj.md @@ -1 +1,15 @@ -# Databases \ No newline at end of file +# Databases + +A database is a collection of useful data of one or more related organizations structured in a way to make data an asset to the organization. A database management system is a software designed to assist in maintaining and extracting large collections of data in a timely fashion. Some of the most commonly used databases include: + +- Relational databases +- NoSQL databases +- In-memory databases +- Embedded databases +- Cloud-based databases + +Each database type has its own set of features and use cases, and the choice of which database to use will depend on the specific requirements of the application. + +Visit the following resources to learn more: + +- [@article@What is a Database?](ttps://www.oracle.com/database/what-is-database/) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/dbt@-KzusmyDQ1NgqOADpqmEX.md b/src/data/roadmaps/bi-analyst/content/dbt@-KzusmyDQ1NgqOADpqmEX.md index e1b1415a7..9a161b140 100644 --- a/src/data/roadmaps/bi-analyst/content/dbt@-KzusmyDQ1NgqOADpqmEX.md +++ b/src/data/roadmaps/bi-analyst/content/dbt@-KzusmyDQ1NgqOADpqmEX.md @@ -1 +1,9 @@ -# dbt \ No newline at end of file +# dbt + +dbt, also known as the data build tool, is designed to simplify the management of data warehouses and transform the data within. This is primarily the T, or transformation, within ELT (or sometimes ETL) processes. It allows for easy transition between data warehouse types, such as Snowflake, BigQuery, Postgres, or DuckDB. dbt also provides the ability to use SQL across teams of multiple users, simplifying interaction. In addition, dbt translates between SQL dialects as appropriate to connect to different data sources and warehouses. + +Visit the following resources to learn more: + +- [@official@dbt](https://www.getdbt.com/product/what-is-dbt) +- [@official@dbt Docs](https://docs.getdbt.com/docs/build/documentation) +- [@course@dbt Official Course](https://learn.getdbt.com/catalog) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/descriptive-analysis@vTW3jSZ1bvc0OrP_bl22t.md b/src/data/roadmaps/bi-analyst/content/descriptive-analysis@vTW3jSZ1bvc0OrP_bl22t.md index 690b577a6..40dcaa67f 100644 --- a/src/data/roadmaps/bi-analyst/content/descriptive-analysis@vTW3jSZ1bvc0OrP_bl22t.md +++ b/src/data/roadmaps/bi-analyst/content/descriptive-analysis@vTW3jSZ1bvc0OrP_bl22t.md @@ -1 +1,8 @@ -# Descriptive Analysis \ No newline at end of file +# Descriptive Analytics + +Descriptive Analytics is one of the fundamental types of Data Analytics that provides insight into the past. As a Data Analyst, utilizing Descriptive Analytics involves the technique of using historical data to understand changes that have occurred in a business over time. Primarily concerned with the “what has happened” aspect, it analyzes raw data from the past to draw inferences and identify patterns and trends. This helps companies understand their strengths, weaknesses and pinpoint operational problems, setting the stage for accurate Business Intelligence and decision-making processes. + +Visit the following resources to learn more: + +- [@article@Descriptive Analytics: What They Are and Related Terms](https://www.investopedia.com/terms/d/descriptive-analytics.asp) +- [@article@What are Descriptive Analytics?](https://www.youtube.com/watch?v=DlFqQy10aCs) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/descriptive-statistics@xc1hm_XTyiMUVtWiTKXWG.md b/src/data/roadmaps/bi-analyst/content/descriptive-statistics@xc1hm_XTyiMUVtWiTKXWG.md index ac90187b7..b52e3400a 100644 --- a/src/data/roadmaps/bi-analyst/content/descriptive-statistics@xc1hm_XTyiMUVtWiTKXWG.md +++ b/src/data/roadmaps/bi-analyst/content/descriptive-statistics@xc1hm_XTyiMUVtWiTKXWG.md @@ -1 +1,9 @@ -# Descriptive Statistics \ No newline at end of file +# Descriptive Statistics + +Descriptive statistics are methods used to summarize and describe the main features of a dataset. This involves calculating measures like mean, median, and mode to represent central tendency, as well as measures like standard deviation and range to describe the spread or variability of the data. These techniques help to gain initial insights into the data's distribution and characteristics without making inferences beyond the observed sample. + +Visit the following resources to learn more: + +- [@article@Descriptive Statistics: Definition, Overview, Types, and Examples](https://www.investopedia.com/terms/d/descriptive_statistics.asp) +- [@article@Descriptive statistics](https://en.wikipedia.org/wiki/Descriptive_statistics) +- [@article@Intro to Statistics](https://www.udacity.com/course/intro-to-statistics--st101) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/design-principles@EDQjtoTd01ftwXxYkV9it.md b/src/data/roadmaps/bi-analyst/content/design-principles@EDQjtoTd01ftwXxYkV9it.md index abb0c6c9d..bb025ff98 100644 --- a/src/data/roadmaps/bi-analyst/content/design-principles@EDQjtoTd01ftwXxYkV9it.md +++ b/src/data/roadmaps/bi-analyst/content/design-principles@EDQjtoTd01ftwXxYkV9it.md @@ -1 +1,7 @@ -# Design principles \ No newline at end of file +# Design Principles for Data Visualization + +Effective data visualization design principles include Clarity, Simplicity, Accuracy, and Consistency, ensuring your visuals are easy to understand and don't mislead the audience. Also important are the context (i.e. providing enough information to understand the data); choosing the right chart type to best tell the story; and applying Design Principles like balance, contrast, and emphasis to create engaging and effective visuals. + +Visit the following resources to learn more: + +- [@article@10 Essential Data Visualization Design Principles for Clearer Insights](https://www.tenscope.com/post/data-visualization-design-principles-for-clarity) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/diagnostic-analysis@m5aC9aNy9mwLXz0xXBp40.md b/src/data/roadmaps/bi-analyst/content/diagnostic-analysis@m5aC9aNy9mwLXz0xXBp40.md index cb6f5d5f8..896c9a5db 100644 --- a/src/data/roadmaps/bi-analyst/content/diagnostic-analysis@m5aC9aNy9mwLXz0xXBp40.md +++ b/src/data/roadmaps/bi-analyst/content/diagnostic-analysis@m5aC9aNy9mwLXz0xXBp40.md @@ -1 +1,8 @@ -# Diagnostic Analysis \ No newline at end of file +# Diagnostic Analytics + +Diagnostic analytics, as a crucial type of data analytics, is focused on studying past performance to understand why something happened. This is an integral part of the work done by data analysts. Through techniques such as drill-down, data discovery, correlations, and cause-effect analysis, data analysts utilizing diagnostic analytics can look beyond general trends and identify the root cause of changes observed in the data. Consequently, this enables businesses to address operational and strategic issues effectively, by allowing them to grasp the reasons behind such issues. For every data analyst, the skill of performing diagnostic data analytics is a must-have asset that enhances their analysis capability. + +Visit the following resources to learn more: + +- [@article@hat is Diagnostic Analytics?](https://amplitude.com/explore/analytics/what-diagnostic-analytics) +- [@video@What is Diagnostic Analytics? | Understanding Data-Driven Decision Making](https://www.youtube.com/watch?v=ikZjeAC1yJ0) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/discrete-vs-continuous@YSxvg2HrfGoGtpkwY0kGc.md b/src/data/roadmaps/bi-analyst/content/discrete-vs-continuous@YSxvg2HrfGoGtpkwY0kGc.md index d1628c809..416f843dc 100644 --- a/src/data/roadmaps/bi-analyst/content/discrete-vs-continuous@YSxvg2HrfGoGtpkwY0kGc.md +++ b/src/data/roadmaps/bi-analyst/content/discrete-vs-continuous@YSxvg2HrfGoGtpkwY0kGc.md @@ -1 +1,8 @@ -# Discrete vs Continuous \ No newline at end of file +# Discrete vs. Continuous Variables + +Discrete variables represent countable items, meaning they can only take on specific, separate values (like whole numbers). Continuous variables, on the other hand, can take on any value within a given range, including fractions and decimals. Understanding the difference is crucial for choosing the right statistical methods and interpreting data accurately. + +Visit the following resources to learn more: + +- [@article@Continuous or discrete variable](https://en.wikipedia.org/wiki/Continuous_or_discrete_variable) +- [@article@Intro to Statistics](https://www.udacity.com/course/intro-to-statistics--st101) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/dispersion@1D98k1HNCaaiaI20euVwA.md b/src/data/roadmaps/bi-analyst/content/dispersion@1D98k1HNCaaiaI20euVwA.md index 59af953e2..1a7aec461 100644 --- a/src/data/roadmaps/bi-analyst/content/dispersion@1D98k1HNCaaiaI20euVwA.md +++ b/src/data/roadmaps/bi-analyst/content/dispersion@1D98k1HNCaaiaI20euVwA.md @@ -1 +1,7 @@ -# Dispersion \ No newline at end of file +Dispersion measures offers a crucial way to understand the variability or spread in a set of data. Distinct measures of dispersion such as range, variance, standard deviation, and interquartile range gives BI analysts insight into how spread out data points are, and how reliable any patterns detected may be. This understanding of dispersion helps data analysts in identifying outliers, drawing meaningful conclusions, and making informed predictions. + +Visit the following resources to learn more: + +- [@article@What is dispersion?](https://www.investopedia.com/terms/d/dispersion.asp) +- [@video@Statistics 101 - Measures of Dispersion](https://www.youtube.com/watch?v=goXdWMZxlqM) +- [@article@Intro to Statistics](https://www.udacity.com/course/intro-to-statistics--st101) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/distribution@JSqwWsfojjZTe8ynmA7fc.md b/src/data/roadmaps/bi-analyst/content/distribution@JSqwWsfojjZTe8ynmA7fc.md index a8994647f..fd7084f0c 100644 --- a/src/data/roadmaps/bi-analyst/content/distribution@JSqwWsfojjZTe8ynmA7fc.md +++ b/src/data/roadmaps/bi-analyst/content/distribution@JSqwWsfojjZTe8ynmA7fc.md @@ -1 +1,8 @@ -# Distribution \ No newline at end of file +# Distribution + +Two additional statistics to better understand the distribution of your datasets are skewness and kurtosis, which measures distribution asymetry, whereas kurtosis measurs the "tailedness" and peakedness of a distribution. + +Visit the following resources to learn more: + +- [@article@Understanding Skewness And Kurtosis And How to Plot Them](https://www.datacamp.com/tutorial/understanding-skewness-and-kurtosis) +- [@article@Intro to Statistics](https://www.udacity.com/course/intro-to-statistics--st101) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/dplyr@ZAhjB_ghHukD4RPAtNDxh.md b/src/data/roadmaps/bi-analyst/content/dplyr@ZAhjB_ghHukD4RPAtNDxh.md index 6423037af..396537f5c 100644 --- a/src/data/roadmaps/bi-analyst/content/dplyr@ZAhjB_ghHukD4RPAtNDxh.md +++ b/src/data/roadmaps/bi-analyst/content/dplyr@ZAhjB_ghHukD4RPAtNDxh.md @@ -1 +1,8 @@ -# dplyr \ No newline at end of file +# dplyr for Exploratory Data Analysis + +dplyr is an R package that makes data manipulation and exploration easier. It provides a consistent set of verbs, like `filter`, `select`, `mutate`, `summarize`, and `arrange`, that allow you to quickly perform common data analysis tasks. These functions are designed to be intuitive and work together seamlessly, letting you chain operations to efficiently clean, transform, and gain insights from your data. This streamlined approach helps you understand your data's structure, identify patterns, and prepare it for further analysis or visualization. + +Visit the following resources to learn more: + +- [@official@dplyr](https://dplyr.tidyverse.org/) +- [@article@Exploratory Data Analysis with dplyr](https://www.gastonsanchez.com/intro2cwd/eda-dplyr.html) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/duplicates@xjgqmJmetKpWXSWZHPwaL.md b/src/data/roadmaps/bi-analyst/content/duplicates@xjgqmJmetKpWXSWZHPwaL.md index e252539ac..9b7df96b8 100644 --- a/src/data/roadmaps/bi-analyst/content/duplicates@xjgqmJmetKpWXSWZHPwaL.md +++ b/src/data/roadmaps/bi-analyst/content/duplicates@xjgqmJmetKpWXSWZHPwaL.md @@ -1 +1,7 @@ -# Duplicates \ No newline at end of file +# Duplicate Data + +Duplicate data refers to instances where the same piece of information is repeated within a dataset. This can occur due to various reasons, such as human error during data entry, system glitches, or integration of data from multiple sources. Identifying and removing or merging these duplicates is crucial for ensuring data accuracy and reliability. + +Visit the following resources to learn more: + +- [@article@Data Duplication Implications and Solutions](https://www.oracle.com/uk/data-duplication/) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/end-to-end-analytics-project@3xDVJwdl3uu5EcjlZ1ytA.md b/src/data/roadmaps/bi-analyst/content/end-to-end-analytics-project@3xDVJwdl3uu5EcjlZ1ytA.md index 737928594..0fdf618ef 100644 --- a/src/data/roadmaps/bi-analyst/content/end-to-end-analytics-project@3xDVJwdl3uu5EcjlZ1ytA.md +++ b/src/data/roadmaps/bi-analyst/content/end-to-end-analytics-project@3xDVJwdl3uu5EcjlZ1ytA.md @@ -1 +1,8 @@ -# End-to-end Analytics Project \ No newline at end of file +# End-to-End Analytics Project + +An end-to-end analytics project encompasses the entire process of solving a business problem using data. This involves defining the problem, gathering and cleaning data, performing exploratory data analysis, building and deploying a model or visualization, and communicating the results and recommendations to stakeholders. It demonstrates a comprehensive understanding of the analytics lifecycle. + +Visit the following resources to learn more: + +- [@article@20 Data Analytics Projects for All Levels](https://www.datacamp.com/blog/data-analytics-projects-all-levels) +- [@video@End to End Data Analytics Project (Python + SQL)](https://www.youtube.com/watch?v=uL0-6kfiH3g) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/ethical-data-use@Vb06K0D2vWAlSe95QJrth.md b/src/data/roadmaps/bi-analyst/content/ethical-data-use@Vb06K0D2vWAlSe95QJrth.md index 5f23cc3b3..e27a5ed89 100644 --- a/src/data/roadmaps/bi-analyst/content/ethical-data-use@Vb06K0D2vWAlSe95QJrth.md +++ b/src/data/roadmaps/bi-analyst/content/ethical-data-use@Vb06K0D2vWAlSe95QJrth.md @@ -1 +1,8 @@ -# Ethical Data Use \ No newline at end of file +# Ethical Data Use + +Ethical data use refers to the responsible and morally sound application of data in decision-making processes. It involves considering the potential impact of data analysis and insights on individuals, groups, and society as a whole, ensuring fairness, transparency, and accountability. This includes respecting privacy, avoiding bias, and using data in ways that promote positive outcomes while minimizing harm. + +Visit the following resources to learn more: + +- [@article@An Introduction to Data Ethics: What is the Ethical Use of Data?](https://www.datacamp.com/blog/introduction-to-data-ethics) +- [@article@5 Principles of Data Ethics for Business](https://online.hbs.edu/blog/post/data-ethics) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/etl-basics@Du4GD-6pxbWYl4uSJRnOE.md b/src/data/roadmaps/bi-analyst/content/etl-basics@Du4GD-6pxbWYl4uSJRnOE.md index 96f8312cf..98fc8c672 100644 --- a/src/data/roadmaps/bi-analyst/content/etl-basics@Du4GD-6pxbWYl4uSJRnOE.md +++ b/src/data/roadmaps/bi-analyst/content/etl-basics@Du4GD-6pxbWYl4uSJRnOE.md @@ -1 +1,9 @@ -# ETL basics \ No newline at end of file +# ETL Basics + +ETL, which stands for Extract, Transform, and Load, is a process used to move data from various source systems into a data warehouse or other data repository. It involves extracting data from different sources, transforming it into a consistent and usable format, and then loading it into the target system for analysis and reporting. This process ensures data quality and consistency, making it easier to derive meaningful insights. + +Visit the following resources to learn more: + +- [@article@What is ETL?](https://www.snowflake.com/guides/what-etl) +- [@video@ETL Explained](https://www.youtube.com/watch?v=OW5OgsLpDCQ) +- [@feed@Explore top posts about ETL](https://app.daily.dev/tags/etl?ref=roadmapsh) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/etl-tools@lAK9QVs97hL3ysjz2blp8.md b/src/data/roadmaps/bi-analyst/content/etl-tools@lAK9QVs97hL3ysjz2blp8.md index e57f8ae76..c40dfa2cc 100644 --- a/src/data/roadmaps/bi-analyst/content/etl-tools@lAK9QVs97hL3ysjz2blp8.md +++ b/src/data/roadmaps/bi-analyst/content/etl-tools@lAK9QVs97hL3ysjz2blp8.md @@ -1 +1,3 @@ -# ETL Tools \ No newline at end of file +# ETL Tools + +ETL (Extract, Transform, Load) tools are software applications used to move data from various source systems into a data warehouse or other target system. These tools extract data from different sources, transform it into a consistent and usable format, and then load it into the destination system for analysis and reporting. This process ensures data quality and consistency, making it easier for business intelligence analysts to derive meaningful insights. \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/excel@9BWyA0b4WrmQetSMph_mY.md b/src/data/roadmaps/bi-analyst/content/excel@9BWyA0b4WrmQetSMph_mY.md index 571ece0c4..fc49a8b4b 100644 --- a/src/data/roadmaps/bi-analyst/content/excel@9BWyA0b4WrmQetSMph_mY.md +++ b/src/data/roadmaps/bi-analyst/content/excel@9BWyA0b4WrmQetSMph_mY.md @@ -1 +1,8 @@ -# Excel \ No newline at end of file +# Excel for Exploratory Data Analysis + +Excel is a readily available and user-friendly tool that's great for getting a first look at your data. It allows you to quickly sort, filter, and calculate basic statistics like averages and sums. You can also create simple charts and graphs to visualize trends and patterns, helping you understand your data's main characteristics and identify potential areas for deeper investigation, all without needing specialized programming knowledge. + +Visit the following resources to learn more: + +- [@article@Exploratory Data Analysis in Excel](https://www.scaler.com/topics/exploratory-data-analysis-projects/) +- [@video@Exploratory Data Analysis With Excel](https://www.youtube.com/watch?v=1zEFJHbG0aE&list=PLTJTBoU5HOCRFQhfU1gg2ciNpS_evWKR7) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/excel@Dh62zxyyUHh0galD472p8.md b/src/data/roadmaps/bi-analyst/content/excel@Dh62zxyyUHh0galD472p8.md index 571ece0c4..ef95ecca9 100644 --- a/src/data/roadmaps/bi-analyst/content/excel@Dh62zxyyUHh0galD472p8.md +++ b/src/data/roadmaps/bi-analyst/content/excel@Dh62zxyyUHh0galD472p8.md @@ -1 +1,3 @@ -# Excel \ No newline at end of file +# Excel Files + +Excel files are a common way to store and organize data in a spreadsheet format. They use rows and columns to arrange information, allowing for easy viewing and manipulation. These files can contain various data types like text, numbers, dates, and formulas to perform calculations. Excel files are widely used for data entry, analysis, and reporting due to their user-friendly interface and versatility. \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/excel@LLK3_hudKDX5d-fd98vlx.md b/src/data/roadmaps/bi-analyst/content/excel@LLK3_hudKDX5d-fd98vlx.md index 571ece0c4..12679d125 100644 --- a/src/data/roadmaps/bi-analyst/content/excel@LLK3_hudKDX5d-fd98vlx.md +++ b/src/data/roadmaps/bi-analyst/content/excel@LLK3_hudKDX5d-fd98vlx.md @@ -1 +1,8 @@ -# Excel \ No newline at end of file +# Excel + +Excel is a spreadsheet program used for organizing, analyzing, and storing data in tables. It allows users to perform calculations, create charts and graphs, and automate tasks using formulas and macros. It is widely used for data entry, data cleaning, and basic data analysis. + +Visit the following resources to learn more: + +- [@official@Microsoft Excel](https://www.microsoft.com/microsoft-365/) +- [@video@Excel Full Course Tutorial (4+ Hours)](https://www.youtube.com/watch?v=rro5t8eHXaY) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/exploratory-data-analysis-eda@ETT9eATuyLHQe2jPqaF5I.md b/src/data/roadmaps/bi-analyst/content/exploratory-data-analysis-eda@ETT9eATuyLHQe2jPqaF5I.md index 5c6140b32..f32cf032b 100644 --- a/src/data/roadmaps/bi-analyst/content/exploratory-data-analysis-eda@ETT9eATuyLHQe2jPqaF5I.md +++ b/src/data/roadmaps/bi-analyst/content/exploratory-data-analysis-eda@ETT9eATuyLHQe2jPqaF5I.md @@ -1 +1,8 @@ -# Exploratory Data Analysis (EDA) \ No newline at end of file +# Exploratory Data Analysis (EDA) + +Exploratory Data Analysis (EDA) is an approach to analyzing data sets to summarize their main characteristics, often with visual methods. It's used to discover patterns, spot anomalies, test hypotheses, and check assumptions with the help of summary statistics and graphical representations. The goal of EDA is to gain a deeper understanding of the data before formal modelling or hypothesis testing. + +Visit the following resources to learn more: + +- [@article@What is Exploratory Data Analysis?](https://www.ibm.com/think/topics/exploratory-data-analysis) +- [@video@Exploratory Data Analysis](https://www.youtube.com/watch?v=QiqZliDXCCg) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/fact-vs-dimension-tables@hcbS18cpVxd55hVlUeLLT.md b/src/data/roadmaps/bi-analyst/content/fact-vs-dimension-tables@hcbS18cpVxd55hVlUeLLT.md index dee0eb074..595b780ab 100644 --- a/src/data/roadmaps/bi-analyst/content/fact-vs-dimension-tables@hcbS18cpVxd55hVlUeLLT.md +++ b/src/data/roadmaps/bi-analyst/content/fact-vs-dimension-tables@hcbS18cpVxd55hVlUeLLT.md @@ -1 +1,7 @@ -# Fact vs Dimension Tables \ No newline at end of file +# Fact vs Dimension Tables + +Fact tables store quantitative data (facts) about business events, like sales or website visits. These tables are typically large and contain foreign keys referencing dimension tables. Dimension tables, on the other hand, store descriptive attributes about the facts, such as customer details, product information, or dates. They provide context for analyzing the facts in the fact table. + +Visit the following resources to learn more: + +- [@article@Fact Table vs Dimension Table: What's the Difference](https://www.simplilearn.com/fact-table-vs-dimension-table-article) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/finance@cxTriSZvrmXP4axKynIZW.md b/src/data/roadmaps/bi-analyst/content/finance@cxTriSZvrmXP4axKynIZW.md index bc15c9c78..428c0dc99 100644 --- a/src/data/roadmaps/bi-analyst/content/finance@cxTriSZvrmXP4axKynIZW.md +++ b/src/data/roadmaps/bi-analyst/content/finance@cxTriSZvrmXP4axKynIZW.md @@ -1 +1,3 @@ -# Finance \ No newline at end of file +# Finance + +Finance encompasses the activities related to managing money and investments. It involves planning, organizing, controlling, and monitoring financial resources to achieve organizational goals. Key areas within finance include budgeting, financial planning, investment management, and risk management, all aimed at ensuring the financial health and stability of a business. \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/finance@xftv5BiyoVrFjpSN0tjsw.md b/src/data/roadmaps/bi-analyst/content/finance@xftv5BiyoVrFjpSN0tjsw.md index bc15c9c78..8ae260afb 100644 --- a/src/data/roadmaps/bi-analyst/content/finance@xftv5BiyoVrFjpSN0tjsw.md +++ b/src/data/roadmaps/bi-analyst/content/finance@xftv5BiyoVrFjpSN0tjsw.md @@ -1 +1,3 @@ -# Finance \ No newline at end of file +# BI Applications in Finance + +Business Intelligence tools help analyze large datasets to improve decision-making in the finance sector. They are used to track financial performance, identify trends, manage risk, and detect fraud. BI applications provide insights into profitability, customer behavior, and operational efficiency, enabling financial institutions to optimize their strategies and improve their bottom line. \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/financial-performance@1T2PyytlmndHreWgueD55.md b/src/data/roadmaps/bi-analyst/content/financial-performance@1T2PyytlmndHreWgueD55.md index ee4f3b872..8fb09fd0c 100644 --- a/src/data/roadmaps/bi-analyst/content/financial-performance@1T2PyytlmndHreWgueD55.md +++ b/src/data/roadmaps/bi-analyst/content/financial-performance@1T2PyytlmndHreWgueD55.md @@ -1 +1,7 @@ -# Financial Performance \ No newline at end of file +# Financial Performance + +Financial performance refers to how well a company uses its assets to generate revenue. It's measured through various financial metrics and ratios that provide insights into a company's profitability, efficiency, solvency, and liquidity. Analyzing financial performance helps stakeholders understand the overall health and sustainability of a business. + +Visit the following resources to learn more: + +- [@article@Financial Performance: Definition, How It Works, and Example](https://www.investopedia.com/terms/f/financialperformance.asp#:~:text=A%20financial%20performance%20analysis%20examines,statements%20used%20in%20performance%20analysis.) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/forecasting@ExHCSUDxDBwsJtTelvxjP.md b/src/data/roadmaps/bi-analyst/content/forecasting@ExHCSUDxDBwsJtTelvxjP.md index 190afd63d..d7c176b5c 100644 --- a/src/data/roadmaps/bi-analyst/content/forecasting@ExHCSUDxDBwsJtTelvxjP.md +++ b/src/data/roadmaps/bi-analyst/content/forecasting@ExHCSUDxDBwsJtTelvxjP.md @@ -1 +1,7 @@ -# Forecasting \ No newline at end of file +# Forecasting + +Forecasting is a technique used to predict future values based on historical data. It involves analyzing past trends and patterns to estimate what is likely to happen in the future. This can be done using various statistical methods and algorithms, taking into account factors like seasonality, trends, and cyclical patterns to generate informed predictions. + +Visit the following resources to learn more: + +- [@video@Complete Time Series Analysis and Forecasting with Python](https://www.youtube.com/watch?v=eKiXtGzEjos) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/fraud-detection@aJLGan5dkMefvkspFlcYo.md b/src/data/roadmaps/bi-analyst/content/fraud-detection@aJLGan5dkMefvkspFlcYo.md index e48d5950d..06625bc93 100644 --- a/src/data/roadmaps/bi-analyst/content/fraud-detection@aJLGan5dkMefvkspFlcYo.md +++ b/src/data/roadmaps/bi-analyst/content/fraud-detection@aJLGan5dkMefvkspFlcYo.md @@ -1 +1,8 @@ -# Fraud Detection \ No newline at end of file +# Fraud Detection + +Fraud detection involves identifying and preventing deceptive or illegal activities in financial transactions. It uses data analysis techniques to spot patterns and anomalies that deviate from normal behavior, helping organizations minimize financial losses and maintain integrity. This process often involves analyzing large datasets of transactions, customer information, and other relevant data to flag suspicious activities for further investigation. + +Visit the following resources to learn more: + +- [@article@What Is Fraud Analytics and How to Use Data for Fraud Detection?](https://www.feedzai.com/blog/fraud-data-analytics/) +- [@article@Data analysis for fraud detection](https://en.wikipedia.org/wiki/Data_analysis_for_fraud_detection) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/gdpr@CWf_vL78f8-mSUQbPnU8e.md b/src/data/roadmaps/bi-analyst/content/gdpr@CWf_vL78f8-mSUQbPnU8e.md index 7eeee7f65..5c585ea2f 100644 --- a/src/data/roadmaps/bi-analyst/content/gdpr@CWf_vL78f8-mSUQbPnU8e.md +++ b/src/data/roadmaps/bi-analyst/content/gdpr@CWf_vL78f8-mSUQbPnU8e.md @@ -1 +1,9 @@ -# GDPR \ No newline at end of file +# GDPR + +The General Data Protection Regulation (GDPR) is a European Union law focused on protecting the privacy and personal data of individuals within the EU and the European Economic Area (EEA). It dictates how organizations collect, use, and store personal information, giving individuals more control over their data and imposing strict rules on data processing activities. GDPR aims to standardize data protection laws across Europe and applies to any organization that processes the personal data of EU residents, regardless of the organization's location. + +Visit the following resources to learn more: + +- [@official@GPDR](https://gdpr-info.eu/) +- [@article@What is GDPR, the EU’s new data protection law?](https://gdpr.eu/what-is-gdpr/) +- [@article@EU GDPR summary |What is the GDPR?](https://www.youtube.com/watch?v=I-VuonciKWk) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/healthcare@VpGVezYr9O6puhAF12PN2.md b/src/data/roadmaps/bi-analyst/content/healthcare@VpGVezYr9O6puhAF12PN2.md index 55391903b..71eb59173 100644 --- a/src/data/roadmaps/bi-analyst/content/healthcare@VpGVezYr9O6puhAF12PN2.md +++ b/src/data/roadmaps/bi-analyst/content/healthcare@VpGVezYr9O6puhAF12PN2.md @@ -1 +1,7 @@ -# Healthcare \ No newline at end of file +# Healthcare + +Business Intelligence can be a game-changer in healthcare, helping hospitals, clinics, and other medical organizations make better decisions. It involves collecting and analyzing data from various sources, like patient records, insurance claims, and operational systems. This data is then used to identify trends, improve patient care, optimize resource allocation, reduce costs, and enhance overall efficiency within the healthcare system. + +Visit the following resources to learn more: + +- [@article@What Is Health Care Business Intelligence?](https://www.coursera.org/articles/healthcare-business-intelligence) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/heatmap@SNkYi2VZsCRG31v63v8_x.md b/src/data/roadmaps/bi-analyst/content/heatmap@SNkYi2VZsCRG31v63v8_x.md index d8aede0d9..205255458 100644 --- a/src/data/roadmaps/bi-analyst/content/heatmap@SNkYi2VZsCRG31v63v8_x.md +++ b/src/data/roadmaps/bi-analyst/content/heatmap@SNkYi2VZsCRG31v63v8_x.md @@ -1 +1,3 @@ -# Heatmap \ No newline at end of file +# Heatmaps + +A heatmap is a graphical representation of data where values are depicted using color. It allows you to quickly identify patterns, correlations, and variations in large datasets by representing data points as colored cells in a matrix. The color intensity typically corresponds to the magnitude of the value, making it easy to spot high and low values at a glance. \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/histogram@wqLcUFVsLa_l9yQIee9MG.md b/src/data/roadmaps/bi-analyst/content/histogram@wqLcUFVsLa_l9yQIee9MG.md index 740334e1d..776860b82 100644 --- a/src/data/roadmaps/bi-analyst/content/histogram@wqLcUFVsLa_l9yQIee9MG.md +++ b/src/data/roadmaps/bi-analyst/content/histogram@wqLcUFVsLa_l9yQIee9MG.md @@ -1 +1,3 @@ -# Histogram \ No newline at end of file +# Histogram + +A histogram is a type of bar chart that visually represents the distribution of numerical data. It groups data into bins (or intervals) and displays the frequency (or count) of data points falling within each bin. This allows you to quickly understand the underlying frequency distribution, identify patterns like skewness or outliers, and gain insights into the central tendency and spread of the data. \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/hospital-efficiency@ku3m0ZmNg23F0Z5CEb4JI.md b/src/data/roadmaps/bi-analyst/content/hospital-efficiency@ku3m0ZmNg23F0Z5CEb4JI.md index acc96c567..e4a2e39d9 100644 --- a/src/data/roadmaps/bi-analyst/content/hospital-efficiency@ku3m0ZmNg23F0Z5CEb4JI.md +++ b/src/data/roadmaps/bi-analyst/content/hospital-efficiency@ku3m0ZmNg23F0Z5CEb4JI.md @@ -1 +1,7 @@ -# Hospital Efficiency \ No newline at end of file +# Improving Hospital Efficiency with Data Analytics + +Data analytics can help hospitals run smoother and provide better care. By looking at data on patient flow, staffing levels, and resource usage, hospitals can identify bottlenecks and areas for improvement. For example, analyzing wait times in the emergency room can reveal patterns that suggest the need for more staff during peak hours. Similarly, tracking the use of medical equipment can help hospitals optimize inventory and reduce waste. Ultimately, data-driven insights enable hospitals to make informed decisions that improve efficiency, reduce costs, and enhance patient outcomes. + +Visit the following resources to learn more: + +- [@article@Improving Hospital Efficiency with Health Data Analytics](https://futuramo.com/blog/improving-hospital-efficiency-with-health-data-analytics/) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/hr@KeGCHoJRHp-mBX-P5to4Y.md b/src/data/roadmaps/bi-analyst/content/hr@KeGCHoJRHp-mBX-P5to4Y.md index ffcf28fde..448d511d6 100644 --- a/src/data/roadmaps/bi-analyst/content/hr@KeGCHoJRHp-mBX-P5to4Y.md +++ b/src/data/roadmaps/bi-analyst/content/hr@KeGCHoJRHp-mBX-P5to4Y.md @@ -1 +1,3 @@ -# HR \ No newline at end of file +# Human Resources (HR) + +Human Resources (HR) is the area within a company responsible for managing employees. This includes recruiting, hiring, training, and developing employees, as well as handling compensation, benefits, and employee relations. HR ensures legal compliance with labor laws and company policies, and aims to create a positive and productive work environment. \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/hypothesis-testing@6xfQic8dMwUsMQa7VtS8_.md b/src/data/roadmaps/bi-analyst/content/hypothesis-testing@6xfQic8dMwUsMQa7VtS8_.md index b8c67a193..dbecb0e76 100644 --- a/src/data/roadmaps/bi-analyst/content/hypothesis-testing@6xfQic8dMwUsMQa7VtS8_.md +++ b/src/data/roadmaps/bi-analyst/content/hypothesis-testing@6xfQic8dMwUsMQa7VtS8_.md @@ -1 +1,9 @@ -# Hypothesis Testing \ No newline at end of file +# Hypothesis Testing + +Hypothesis testing is a statistical method used to determine whether there is enough evidence in a sample of data to infer that a certain condition is true for an entire population. It involves formulating a null hypothesis (a statement of no effect or no difference) and an alternative hypothesis (a statement that contradicts the null hypothesis), then using sample data to assess the likelihood of observing the data if the null hypothesis were true. Based on this likelihood, a decision is made to either reject the null hypothesis in favor of the alternative or fail to reject the null hypothesis. + +Visit the following resources to learn more: + +- [@article@Hypothesis Testing](https://latrobe.libguides.com/maths/hypothesis-testing) +- [@article@Hypothesis Testing - 4 Steps](https://www.investopedia.com/terms/h/hypothesistesting.asp) +- [@article@Intro to Inferential Statistics](https://www.udacity.com/course/intro-to-inferential-statistics--ud201) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/inferential-statistics@7DNtRMBZ_F0K1FQk-UCM4.md b/src/data/roadmaps/bi-analyst/content/inferential-statistics@7DNtRMBZ_F0K1FQk-UCM4.md index 9e82cb282..b90b9aa98 100644 --- a/src/data/roadmaps/bi-analyst/content/inferential-statistics@7DNtRMBZ_F0K1FQk-UCM4.md +++ b/src/data/roadmaps/bi-analyst/content/inferential-statistics@7DNtRMBZ_F0K1FQk-UCM4.md @@ -1 +1,10 @@ -# Inferential Statistics \ No newline at end of file +# Inferential Statistics + +Inferential statistics uses sample data to make inferences or predictions about a larger population. It involves techniques like hypothesis testing, confidence intervals, and regression analysis to draw conclusions beyond the immediate data set. The goal is to estimate population parameters and assess the likelihood of certain outcomes based on the observed sample. + +Visit the following resources to learn more: + +- [@article@Inferential Statistics | An Easy Introduction & Examples](https://www.scribbr.com/statistics/inferential-statistics/) +- [@article@Statistical inference](https://en.wikipedia.org/wiki/Statistical_inference) +- [@video@Inferential Statistics FULL Tutorial](https://www.youtube.com/watch?v=6E6pB5JFLgM) +- [@course@Intro to Inferential Statistics](https://www.udacity.com/course/intro-to-inferential-statistics--ud201) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/interpretability@uP8MWZqM9Z0i3eDF4Ldxv.md b/src/data/roadmaps/bi-analyst/content/interpretability@uP8MWZqM9Z0i3eDF4Ldxv.md index e9730f9bc..74d3bffde 100644 --- a/src/data/roadmaps/bi-analyst/content/interpretability@uP8MWZqM9Z0i3eDF4Ldxv.md +++ b/src/data/roadmaps/bi-analyst/content/interpretability@uP8MWZqM9Z0i3eDF4Ldxv.md @@ -1 +1,3 @@ -# Interpretability \ No newline at end of file +# Interpretability + +Interpretability refers to the degree to which a human can understand the cause of a decision. In the context of data quality, it means that data should be clear, understandable, and easily interpreted by users. This ensures that insights derived from the data are accurate and can be confidently used for decision-making. \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/interview-preparation@4XM5ikPiHVehEtT4AB-Ea.md b/src/data/roadmaps/bi-analyst/content/interview-preparation@4XM5ikPiHVehEtT4AB-Ea.md index 9bddacd1e..c26179070 100644 --- a/src/data/roadmaps/bi-analyst/content/interview-preparation@4XM5ikPiHVehEtT4AB-Ea.md +++ b/src/data/roadmaps/bi-analyst/content/interview-preparation@4XM5ikPiHVehEtT4AB-Ea.md @@ -1 +1,8 @@ -# Interview preparation \ No newline at end of file +# Interview Preparation + +Interview preparation involves actively preparing for job interviews by practicing common questions, researching the company and role, and refining your communication skills. This process helps you present yourself effectively, demonstrate your qualifications, and increase your confidence during the interview, ultimately improving your chances of landing the job. + +Visit the following resources to learn more: + +- [@article@BI Analyst Interview Questions and Answers (2025)](https://365datascience.com/career-advice/job-interview-tips/bi-analyst-interview-questions/) +- [@video@2 Hour Data Analyst Interview Masterclass](https://www.youtube.com/watch?v=F5v2dRYU5IA) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/inventory-optimization@LkbB0rpS3Du2K7_ogoc34.md b/src/data/roadmaps/bi-analyst/content/inventory-optimization@LkbB0rpS3Du2K7_ogoc34.md index e5d48457c..4ac0b7691 100644 --- a/src/data/roadmaps/bi-analyst/content/inventory-optimization@LkbB0rpS3Du2K7_ogoc34.md +++ b/src/data/roadmaps/bi-analyst/content/inventory-optimization@LkbB0rpS3Du2K7_ogoc34.md @@ -1 +1,8 @@ -# Inventory Optimization \ No newline at end of file +# Inventory Optimization + +Inventory optimization is the process of strategically managing and controlling the flow of goods to minimize costs while meeting customer demand. It involves analyzing historical sales data, forecasting future demand, and considering factors like lead times, storage costs, and potential obsolescence to determine the optimal quantity of each product to keep in stock. The goal is to strike a balance between avoiding stockouts and minimizing excess inventory, ultimately improving profitability and customer satisfaction. + +Visit the following resources to learn more: + +- [@article@6 effective inventory optimization techniques your team should be using](https://www.thoughtspot.com/data-trends/analytics/inventory-optimization-techniques) +- [@article@What Is Inventory Optimization? Benefits and Techniques](https://www.netsuite.com/portal/resource/articles/inventory-management/inventory-optimization.shtml) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/iot@GrwdQldCWu2zWAaNj6LFk.md b/src/data/roadmaps/bi-analyst/content/iot@GrwdQldCWu2zWAaNj6LFk.md index 3c03e60e6..0b4a27726 100644 --- a/src/data/roadmaps/bi-analyst/content/iot@GrwdQldCWu2zWAaNj6LFk.md +++ b/src/data/roadmaps/bi-analyst/content/iot@GrwdQldCWu2zWAaNj6LFk.md @@ -1 +1,3 @@ -# IoT \ No newline at end of file +# IoT Data Sources + +IoT (Internet of Things) data sources refer to the vast array of devices and sensors connected to the internet that generate data. These devices, ranging from smart home appliances and wearable fitness trackers to industrial sensors and connected vehicles, continuously collect and transmit information about their environment or usage. This data can include measurements like temperature, location, pressure, speed, and a multitude of other variables, providing a rich stream of real-time insights. \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/iqr@LEHK7ohKIzKhlGebd0k_j.md b/src/data/roadmaps/bi-analyst/content/iqr@LEHK7ohKIzKhlGebd0k_j.md index aa614faa7..48250201c 100644 --- a/src/data/roadmaps/bi-analyst/content/iqr@LEHK7ohKIzKhlGebd0k_j.md +++ b/src/data/roadmaps/bi-analyst/content/iqr@LEHK7ohKIzKhlGebd0k_j.md @@ -1 +1,8 @@ -# IQR \ No newline at end of file +# Interquartile Range (IQR) + +The Interquartile Range (IQR) is a measure of statistical dispersion, representing the spread of the middle 50% of a dataset. It's calculated as the difference between the third quartile (Q3) and the first quartile (Q1). The IQR is resistant to outliers, making it a robust measure of variability when extreme values are present. + +Visit the following resources to learn more: + +- [@article@Interquartile range](https://en.wikipedia.org/wiki/Interquartile_range) +- [@article@How to Find Interquartile Range (IQR)](https://www.scribbr.com/statistics/interquartile-range/) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/job-preparation@TojDB4o0i2rs7Qcb10k1r.md b/src/data/roadmaps/bi-analyst/content/job-preparation@TojDB4o0i2rs7Qcb10k1r.md index 8cd9bfd30..1557de02d 100644 --- a/src/data/roadmaps/bi-analyst/content/job-preparation@TojDB4o0i2rs7Qcb10k1r.md +++ b/src/data/roadmaps/bi-analyst/content/job-preparation@TojDB4o0i2rs7Qcb10k1r.md @@ -1 +1,3 @@ -# Job Preparation \ No newline at end of file +# Job Preparation + +Job preparation involves the steps you take to get ready for the job application and interview process. This includes activities like researching potential employers, tailoring your resume and cover letter to specific job descriptions, practicing common interview questions, and developing your professional network. The goal is to present yourself as a qualified and compelling candidate, increasing your chances of landing a job offer. \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/json@p21d2mEUnTQgWhKFTGS9F.md b/src/data/roadmaps/bi-analyst/content/json@p21d2mEUnTQgWhKFTGS9F.md index 1bea9ccab..be81fcdb7 100644 --- a/src/data/roadmaps/bi-analyst/content/json@p21d2mEUnTQgWhKFTGS9F.md +++ b/src/data/roadmaps/bi-analyst/content/json@p21d2mEUnTQgWhKFTGS9F.md @@ -1 +1,7 @@ -# JSON \ No newline at end of file +# JSON + +JSON (JavaScript Object Notation) is a lightweight, human-readable format for storing and transporting data. It uses a text-based format to represent data objects as attribute-value pairs and arrays, making it easy for both humans and machines to parse and generate. JSON is commonly used for transmitting data in web applications (e.g., sending data from a server to a web browser) and is supported by many programming languages. + +Visit the following resources to learn more: + +- [@article@JSON](https://www.json.org/) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/key-business-functions@PkzUqwT21Owk_TfepFPDm.md b/src/data/roadmaps/bi-analyst/content/key-business-functions@PkzUqwT21Owk_TfepFPDm.md index a7ef98519..c4dd2d832 100644 --- a/src/data/roadmaps/bi-analyst/content/key-business-functions@PkzUqwT21Owk_TfepFPDm.md +++ b/src/data/roadmaps/bi-analyst/content/key-business-functions@PkzUqwT21Owk_TfepFPDm.md @@ -1 +1,3 @@ -# Key Business Functions \ No newline at end of file +# Key Business Functions + +Key business functions are the specialized activities that a company undertakes to operate effectively and achieve its goals. These functions typically include areas like finance, marketing, operations, human resources, sales, nd research & development, each playing a distinct role in the overall success of the organization. Understanding how these functions interact and contribute to the business is crucial for analyzing performance and identifying areas for improvement. \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/kurtosis@jvU1iu2M_y1IH62oUpAeU.md b/src/data/roadmaps/bi-analyst/content/kurtosis@jvU1iu2M_y1IH62oUpAeU.md index 1b1dac921..8f1ad56c4 100644 --- a/src/data/roadmaps/bi-analyst/content/kurtosis@jvU1iu2M_y1IH62oUpAeU.md +++ b/src/data/roadmaps/bi-analyst/content/kurtosis@jvU1iu2M_y1IH62oUpAeU.md @@ -1 +1,8 @@ -# Kurtosis \ No newline at end of file +# Kurtosis + +Kurtosis is a statistical measure of a probability distribution's "tailedness," indicating the extent to which extreme values (outliers) are present compared to a normal distribution. It assesses the presence of both peakedness and heavy/light tails, categorizing distributions as leptokurtic (heavy, long tails and a sharp peak), platykurtic (light, short tails and a flat top), or mesokurtic (similar to a normal distribution). + +Visit the following resources to learn more: + +- [@article@Kurtosis](https://en.wikipedia.org/wiki/Kurtosis) +- [@article@What Is Kurtosis? | Definition, Examples & Formula](https://www.scribbr.com/statistics/kurtosis/) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/linear-regression@4-fpZx8p5iSNI3n4Qtacl.md b/src/data/roadmaps/bi-analyst/content/linear-regression@4-fpZx8p5iSNI3n4Qtacl.md index 8a7912197..04d6530bd 100644 --- a/src/data/roadmaps/bi-analyst/content/linear-regression@4-fpZx8p5iSNI3n4Qtacl.md +++ b/src/data/roadmaps/bi-analyst/content/linear-regression@4-fpZx8p5iSNI3n4Qtacl.md @@ -1 +1,9 @@ -# Linear Regression \ No newline at end of file +# Linear Regression + +Linear regression is a statistical method used to model the relationship between a dependent variable and one or more independent variables by fitting a linear equation to observed data. It aims to find the best-fitting line (in simple linear regression) or plane (in multiple linear regression) that minimizes the difference between the predicted values and the actual values of the dependent variable. This allows for predicting future values or understanding the influence of the independent variables on the dependent variable. + +Visit the following resources to learn more: + +- [@article@What Is Linear Regression?](https://www.ibm.com/think/topics/linear-regression) +- [@article@Linear regression](https://en.wikipedia.org/wiki/Linear_regression) +- [@course@Intro to Inferential Statistics](https://www.udacity.com/course/intro-to-inferential-statistics--ud201) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/lineplot@BVDaFmDat48nN3hj5NE71.md b/src/data/roadmaps/bi-analyst/content/lineplot@BVDaFmDat48nN3hj5NE71.md index 28de629a1..e7f362478 100644 --- a/src/data/roadmaps/bi-analyst/content/lineplot@BVDaFmDat48nN3hj5NE71.md +++ b/src/data/roadmaps/bi-analyst/content/lineplot@BVDaFmDat48nN3hj5NE71.md @@ -1 +1,3 @@ -# Lineplot \ No newline at end of file +# Line Plots + +Line plots are a type of data visualization that displays data points connected by straight lines. They are used to show trends and changes in data over a continuous interval, such as time. Each point on the line represents a specific data value, and the lines connecting the points illustrate the relationship between consecutive values. \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/looker@f4MDT1RUfaICAWzyG2E6T.md b/src/data/roadmaps/bi-analyst/content/looker@f4MDT1RUfaICAWzyG2E6T.md index 68f17547b..4aa77a92c 100644 --- a/src/data/roadmaps/bi-analyst/content/looker@f4MDT1RUfaICAWzyG2E6T.md +++ b/src/data/roadmaps/bi-analyst/content/looker@f4MDT1RUfaICAWzyG2E6T.md @@ -1 +1,8 @@ -# Looker \ No newline at end of file +# Looker + +Looker is a Google cloud-based business intelligence and data analytics platform. It allows users to explore, analyze, and visualize data to gain insights and make data-driven decisions. Looker is known for its ability to connect to various data sources, create custom dashboards, and generate reports. It also facilitates the integration of analytics, visualizations, and relevant information into business processes. + +Visit the following resources to learn more: + +- [@official@ooker business intelligence platform embedded analytics](https://cloud.google.com/looker) +- [@official@What is Looker?](ttps://www.youtube.com/watch?v=EmkNPAzla0Y&pp=0gcJCfwAo7VqN5tD) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/manufacturing@zEGmDHaFa-F81tWqa3i9E.md b/src/data/roadmaps/bi-analyst/content/manufacturing@zEGmDHaFa-F81tWqa3i9E.md index c714525f1..27dac926a 100644 --- a/src/data/roadmaps/bi-analyst/content/manufacturing@zEGmDHaFa-F81tWqa3i9E.md +++ b/src/data/roadmaps/bi-analyst/content/manufacturing@zEGmDHaFa-F81tWqa3i9E.md @@ -1 +1,8 @@ -# Manufacturing \ No newline at end of file +# BI in Manufacturing + +Data analytics and BI in manufacturing involves using data to understand and improve how things are made in industrial settings. It's about collecting information from different parts of the manufacturing process – like production lines, supply chains, and sales – and then analyzing it to find patterns and insights. This helps manufacturers make smarter decisions about things like optimizing production, reducing costs, improving quality, and predicting future demand. + +Visit the following resources to learn more: + +- [@article@What Is Manufacturing Analytics?](http://oracle.com/au/scm/manufacturing/manufacturing-analytics/) +- [@article@The future of manufacturing is powered by data and analytics. Here's why](https://www.weforum.org/stories/2022/09/manufacturing-data-advanced-analytics/) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/map@7_5PBCrsukv81mm7yTpDf.md b/src/data/roadmaps/bi-analyst/content/map@7_5PBCrsukv81mm7yTpDf.md index e0a832930..2f269df7a 100644 --- a/src/data/roadmaps/bi-analyst/content/map@7_5PBCrsukv81mm7yTpDf.md +++ b/src/data/roadmaps/bi-analyst/content/map@7_5PBCrsukv81mm7yTpDf.md @@ -1 +1,3 @@ -# Map \ No newline at end of file +# Maps in Data Visualization + +Maps are visual representations of geographical data, used to display information across different locations. They allow you to see spatial patterns and relationships, such as population density, sales distribution, or resource locations. Different types of maps, like choropleth maps (using color shading) or point maps (using markers), can highlight specific aspects of the data and provide valuable insights based on location. \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/marketing-campaigns@0qRm81lJX_Eb6aJkJMjeL.md b/src/data/roadmaps/bi-analyst/content/marketing-campaigns@0qRm81lJX_Eb6aJkJMjeL.md index 177813525..96196e07f 100644 --- a/src/data/roadmaps/bi-analyst/content/marketing-campaigns@0qRm81lJX_Eb6aJkJMjeL.md +++ b/src/data/roadmaps/bi-analyst/content/marketing-campaigns@0qRm81lJX_Eb6aJkJMjeL.md @@ -1 +1,7 @@ -# Marketing Campaigns \ No newline at end of file +# Marketing Campaigns + +Marketing campaigns are organized efforts to promote a specific business goal, such as increasing brand awareness, driving sales, or launching a new product. These campaigns involve a series of coordinated activities, including advertising, promotions, content creation, and customer engagement, all designed to reach a target audience and achieve measurable results. The success of a marketing campaign is typically evaluated based on key performance indicators (KPIs) like conversion rates, return on investment (ROI), and customer acquisition cost (CAC). + +Visit the following resources to learn more: + +- [@article@What is campaign analytics?](https://hightouch.com/blog/campaign-analytics) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/marketing@s-wUPMaagyRupT2RdfHks.md b/src/data/roadmaps/bi-analyst/content/marketing@s-wUPMaagyRupT2RdfHks.md index a309c3776..b5cc3d3ca 100644 --- a/src/data/roadmaps/bi-analyst/content/marketing@s-wUPMaagyRupT2RdfHks.md +++ b/src/data/roadmaps/bi-analyst/content/marketing@s-wUPMaagyRupT2RdfHks.md @@ -1 +1,3 @@ -# Marketing \ No newline at end of file +# Marketing + +Marketing encompasses the strategies and tactics organizations use to promote and sell their products or services. It involves understanding customer needs, creating compelling messaging, choosing the right channels to reach target audiences, and measuring the effectiveness of campaigns to optimize for better results. Ultimately, marketing aims to drive revenue and build brand awareness. \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/mean@S4XEOd2-PHIHOiiGgKVLJ.md b/src/data/roadmaps/bi-analyst/content/mean@S4XEOd2-PHIHOiiGgKVLJ.md index 3dab543f8..42330746d 100644 --- a/src/data/roadmaps/bi-analyst/content/mean@S4XEOd2-PHIHOiiGgKVLJ.md +++ b/src/data/roadmaps/bi-analyst/content/mean@S4XEOd2-PHIHOiiGgKVLJ.md @@ -1 +1,7 @@ -# Mean \ No newline at end of file +# Mean + +Central tendency refers to the statistical measure that identifies a single value as representative of an entire distribution. The mean or average is one of the most popular and widely used measures of central tendency. For a BI analyst, calculating the mean is a routine task. This single value provides an analyst with a quick snapshot of the data and could be useful for further data manipulation or statistical analysis. Mean is particularly helpful in predicting trends and patterns within voluminous data sets or adjusting influencing factors that may distort the 'true' representation of the data. It is the arithmetic average of a range of values or quantities, computed as the total sum of all the values divided by the total number of values. + +Visit the following resources to learn more: + +- [@article@Arithmetic mean](https://en.wikipedia.org/wiki/Arithmetic_mean) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/median@mfLRVcxvAjqmSG-KBpJ4J.md b/src/data/roadmaps/bi-analyst/content/median@mfLRVcxvAjqmSG-KBpJ4J.md index 15fbd0714..7e83603c2 100644 --- a/src/data/roadmaps/bi-analyst/content/median@mfLRVcxvAjqmSG-KBpJ4J.md +++ b/src/data/roadmaps/bi-analyst/content/median@mfLRVcxvAjqmSG-KBpJ4J.md @@ -1 +1,8 @@ -# Median \ No newline at end of file +# Median + +Median signifies the middle value in a data set when arranged in ascending or descending order. As a data analyst, understanding, calculating, and interpreting the median is crucial. It is especially helpful when dealing with outliers in a dataset as the median is less sensitive to extreme values. Thus, providing a more realistic 'central' value for skewed distributions. This measure is a reliable reflection of the dataset and is widely used in fields like real estate, economics, and finance for data interpretation and decision-making. + +Visit the following resources to learn more: + +- [@article@How to find the median value](https://www.mathsisfun.com/median.html) +- [@article@Median: What It Is and How to Calculate It](https://www.investopedia.com/terms/m/median.asp) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/metrics-and-kpis@c0ywBrs9u7MciWAXSgVVg.md b/src/data/roadmaps/bi-analyst/content/metrics-and-kpis@c0ywBrs9u7MciWAXSgVVg.md index 51c85966b..fd742dd6f 100644 --- a/src/data/roadmaps/bi-analyst/content/metrics-and-kpis@c0ywBrs9u7MciWAXSgVVg.md +++ b/src/data/roadmaps/bi-analyst/content/metrics-and-kpis@c0ywBrs9u7MciWAXSgVVg.md @@ -1,3 +1,8 @@ # Metrics and KPIs -Metrics are quantifiable measurements used to track and assess the status of a specific business process. Key Performance Indicators (KPIs) are a subset of metrics that are critical to the success of an organization and are used to measure progress toward strategic goals. For example, website traffic is a metric, while the conversion rate of website visitors into paying customers is a KPI. Another example is that the number of customer service calls is a metric, while the average resolution time for those calls is a KPI. \ No newline at end of file +Metrics are quantifiable measurements used to track and assess the status of a specific business process. Key Performance Indicators (KPIs) are a subset of metrics that are critical to the success of an organization and are used to measure progress toward strategic goals. For example, website traffic is a metric, while the conversion rate of website visitors into paying customers is a KPI. Another example is that the number of customer service calls is a metric, while the average resolution time for those calls is a KPI. + +Visit the following resources to learn more: + +- [@article@KPIs vs Metrics: Learn The Difference With Tips & Examples](https://www.rib-software.com/en/blogs/kpis-vs-metrics-differences) +- [@video@What are KPIs and Metrics? | Data Fundamental for Beginners](https://www.youtube.com/watch?v=ItZlTixh6Bs&vl=en) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/misleading-charts@qGVDuU9RA9Y5g5vlPd-xq.md b/src/data/roadmaps/bi-analyst/content/misleading-charts@qGVDuU9RA9Y5g5vlPd-xq.md index 08f1a03cf..81dba1276 100644 --- a/src/data/roadmaps/bi-analyst/content/misleading-charts@qGVDuU9RA9Y5g5vlPd-xq.md +++ b/src/data/roadmaps/bi-analyst/content/misleading-charts@qGVDuU9RA9Y5g5vlPd-xq.md @@ -1 +1,8 @@ -# Misleading charts \ No newline at end of file +# Misleading Charts + +Misleading charts are visualizations that distort or misrepresent data, intentionally or unintentionally, leading to incorrect interpretations and flawed conclusions. These charts often employ techniques like truncated axes, inconsistent scales, selective data presentation, or inappropriate chart types to exaggerate or downplay certain trends or comparisons, ultimately undermining the integrity of the data being presented. + +Visit the following resources to learn more: + +- [@article@How To Spot Misleading Charts: Check the Axes](https://www.tableau.com/blog/how-spot-misleading-charts-check-axes) +- [@article@https://www.statisticshowto.com/probability-and-statistics/descriptive-statistics/misleading-graphs/](https://www.statisticshowto.com/probability-and-statistics/descriptive-statistics/misleading-graphs/) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/missing-values@fhreEuoT8ZBRwJqbSGrEZ.md b/src/data/roadmaps/bi-analyst/content/missing-values@fhreEuoT8ZBRwJqbSGrEZ.md index f790d0d3e..29c3fc3df 100644 --- a/src/data/roadmaps/bi-analyst/content/missing-values@fhreEuoT8ZBRwJqbSGrEZ.md +++ b/src/data/roadmaps/bi-analyst/content/missing-values@fhreEuoT8ZBRwJqbSGrEZ.md @@ -1 +1,8 @@ -# Missing Values \ No newline at end of file +# Missing Values + +Missing values are data points that are absent from a dataset. These gaps can occur for various reasons, such as errors during data collection, incomplete surveys, or system malfunctions. Handling missing values is a crucial step in data cleaning to ensure the accuracy and reliability of subsequent analyses and reporting. + +Visit the following resources to learn more: + +- [@article@Data Standardization: How It's Done & Why It's Important](https://www.scribbr.com/statistics/missing-data/) +- [@article@Missing data](https://en.wikipedia.org/wiki/Missing_data) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/mitigation-strategies@5MUwKGfSTKlam8KCG0A1U.md b/src/data/roadmaps/bi-analyst/content/mitigation-strategies@5MUwKGfSTKlam8KCG0A1U.md index 1831fdf39..4281c4289 100644 --- a/src/data/roadmaps/bi-analyst/content/mitigation-strategies@5MUwKGfSTKlam8KCG0A1U.md +++ b/src/data/roadmaps/bi-analyst/content/mitigation-strategies@5MUwKGfSTKlam8KCG0A1U.md @@ -1 +1,9 @@ -# Mitigation Strategies \ No newline at end of file +# Mitigation Strategies for Bias + +Mitigation strategies for bias are the proactive steps taken to reduce or eliminate unfair prejudices within data, algorithms, and decision-making processes. These strategies involve identifying potential sources of bias, implementing techniques to correct or compensate for them, and continuously monitoring outcomes to ensure fairness and equity. The goal is to create more accurate, reliable, and just results by addressing and minimizing the impact of bias. + +Visit the following resources to learn more: + +- [@article@Addressing AI bias: a human-centric approach to fairness](https://www.ey.com/en_us/insights/emerging-technologies/addressing-ai-bias-a-human-centric-approach-to-fairness) +- [@article@When AI Gets It Wrong: Addressing AI Hallucinations and Bias](https://mitsloanedtech.mit.edu/ai/basics/addressing-ai-hallucinations-and-bias/) +- [@video@Algorithmic Bias in AI: What It Is and How to Fix It](https://www.youtube.com/watch?v=og67qeTZPYs) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/mobile-apps@1cC6LKxcncaKg4Jm53pUy.md b/src/data/roadmaps/bi-analyst/content/mobile-apps@1cC6LKxcncaKg4Jm53pUy.md index 6617ace4b..78274bf6b 100644 --- a/src/data/roadmaps/bi-analyst/content/mobile-apps@1cC6LKxcncaKg4Jm53pUy.md +++ b/src/data/roadmaps/bi-analyst/content/mobile-apps@1cC6LKxcncaKg4Jm53pUy.md @@ -1 +1,3 @@ -# Mobile Apps \ No newline at end of file +# Mobile App Data Sources + +Mobile apps generate a wealth of data, encompassing user interactions, device information, and app performance metrics. This data is collected through various methods, including tracking user behavior within the app, monitoring device characteristics like operating system and model, and logging app performance indicators such as crash reports and load times. This information provides valuable insights into user engagement, app functionality, and potential areas for improvement. \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/mobile-responsiveness@7t0WfLLqrD5VJQwIAmXMo.md b/src/data/roadmaps/bi-analyst/content/mobile-responsiveness@7t0WfLLqrD5VJQwIAmXMo.md index f248b00ab..ae7b2d7ba 100644 --- a/src/data/roadmaps/bi-analyst/content/mobile-responsiveness@7t0WfLLqrD5VJQwIAmXMo.md +++ b/src/data/roadmaps/bi-analyst/content/mobile-responsiveness@7t0WfLLqrD5VJQwIAmXMo.md @@ -1 +1,7 @@ -# Mobile-responsiveness \ No newline at end of file +# Mobile-Responsive Visualizations + +Mobile-responsive visualizations are designed to adapt and display correctly on various screen sizes and devices, particularly smartphones and tablets. This ensures that data insights are accessible and easily understandable regardless of the device used to view them, maintaining readability and functionality across different platforms. This involves using techniques like flexible layouts, scalable images, and touch-friendly controls to optimize the viewing experience on smaller screens. + +Visit the following resources to learn more: + +- [@article@4 Key Tips: Creating Mighty Mobile Data Visualizations](https://pagely.com/blog/4-key-tips-creating-mighty-mobile-data-visualizations/) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/mode@DQtznxvW5x4s-zGLpUpNY.md b/src/data/roadmaps/bi-analyst/content/mode@DQtznxvW5x4s-zGLpUpNY.md index f1b332af7..2af10f4c0 100644 --- a/src/data/roadmaps/bi-analyst/content/mode@DQtznxvW5x4s-zGLpUpNY.md +++ b/src/data/roadmaps/bi-analyst/content/mode@DQtznxvW5x4s-zGLpUpNY.md @@ -1 +1,8 @@ -# Mode \ No newline at end of file +# Mode + +The mode, in essence, represents the most frequently occurring value in a dataset. While it may appear simplistic, the mode's ability to identify the most common value can be instrumental in a wide range of scenarios, like market research, customer behavior analysis, or trend identification. For instance, a BI analyst can use the mode to determine the most popular product in a sales dataset or identify the most commonly reported bug in a software bug log. + +Visit the following resources to learn more: + +- [@article@Mode: What is it and how to calculate it](https://www.investopedia.com/terms/m/mode.asp) +- [@article@Mean Median Mode Formula](https://www.cuemath.com/mean-median-mode-formula/) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/mysql@eqnAEp2VT7FD2VDy5WVDP.md b/src/data/roadmaps/bi-analyst/content/mysql@eqnAEp2VT7FD2VDy5WVDP.md index d64b98552..40ab8a911 100644 --- a/src/data/roadmaps/bi-analyst/content/mysql@eqnAEp2VT7FD2VDy5WVDP.md +++ b/src/data/roadmaps/bi-analyst/content/mysql@eqnAEp2VT7FD2VDy5WVDP.md @@ -1 +1,12 @@ -# MySQL \ No newline at end of file +# MySQL + +MySQL is an open-source relational database management system (RDBMS) known for its speed, reliability, and ease of use. It uses SQL (Structured Query Language) for database interactions and supports a range of features for data management, including transactions, indexing, and stored procedures. MySQL is widely used for web applications, data warehousing, and various other applications due to its scalability and flexibility. It integrates well with many programming languages and platforms, and is often employed in conjunction with web servers and frameworks in popular software stacks like LAMP (Linux, Apache, MySQL, PHP/Python/Perl). MySQL is maintained by Oracle Corporation and has a large community and ecosystem supporting its development and use. + +Visit the following resources to learn more: + +- [@official@MySQL](https://www.mysql.com/) +- [@article@MySQL for Developers](ttps://planetscale.com/courses/mysql-for-developers/introduction/course-introduction) +- [@article@MySQL Tutorial](https://www.mysqltutorial.org/) +- [@article@MySQL Complete Course](https://www.youtube.com/watch?v=5OdVJbNCSso) +- [@article@Explore top posts about MySQL](https://app.daily.dev/tags/mysql?ref=roadmapsh) +- [@video@MySQL Full Course](https://www.youtube.com/watch?v=5OdVJbNCSso) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/networking@Q98GaitxocEha4zZ9d254.md b/src/data/roadmaps/bi-analyst/content/networking@Q98GaitxocEha4zZ9d254.md index e159d196c..cc57ef5f9 100644 --- a/src/data/roadmaps/bi-analyst/content/networking@Q98GaitxocEha4zZ9d254.md +++ b/src/data/roadmaps/bi-analyst/content/networking@Q98GaitxocEha4zZ9d254.md @@ -1 +1,3 @@ -# Networking \ No newline at end of file +# Networking + +Networking involves building and maintaining relationships with other professionals. It's about connecting with people in your field, sharing information, and offering support. This can involve attending industry events, joining online communities, or simply reaching out to individuals whose work you admire. \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/normalization-vs-denormalization@Prfa0LUmgxcp52IEObFom.md b/src/data/roadmaps/bi-analyst/content/normalization-vs-denormalization@Prfa0LUmgxcp52IEObFom.md index 19b884b51..90ffc60b7 100644 --- a/src/data/roadmaps/bi-analyst/content/normalization-vs-denormalization@Prfa0LUmgxcp52IEObFom.md +++ b/src/data/roadmaps/bi-analyst/content/normalization-vs-denormalization@Prfa0LUmgxcp52IEObFom.md @@ -1 +1,10 @@ -# Normalization vs Denormalization \ No newline at end of file +# Normalization vs Denormalization + +Database normalization is a process used to organize a database into tables and columns. The idea is that a table should be about a specific topic and that only those columns which support that topic are included. This limits the number of duplicate data contained within your database. This makes the database more flexible by eliminating issues stemming from database modifications. + +Denormalization is the opposite of normalization. It is the process of adding redundant data to a database to improve read performance. This is done by adding duplicate data into multiple tables to avoid expensive joins. This is done at the expense of increased storage and decreased write performance. + +Visit the following resources to learn more: + +- [@article@Normalization vs. Denormalization in databases](https://codilime.com/blog/normalization-vs-denormalization-in-databases/) +- [@video@Normalization vs. Denormalization | Events and Event Streaming](https://www.youtube.com/watch?v=sDU94hraq8g) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/open-source-projects@YovS5Dbcr6g_8PMr8jp5t.md b/src/data/roadmaps/bi-analyst/content/open-source-projects@YovS5Dbcr6g_8PMr8jp5t.md index f7e9ea23f..5aa117c41 100644 --- a/src/data/roadmaps/bi-analyst/content/open-source-projects@YovS5Dbcr6g_8PMr8jp5t.md +++ b/src/data/roadmaps/bi-analyst/content/open-source-projects@YovS5Dbcr6g_8PMr8jp5t.md @@ -1 +1,8 @@ -# Open-Source Projects \ No newline at end of file +# Open-Source Projects + +Open-source projects are collaborative software development initiatives where the source code is freely available for anyone to use, modify, and distribute. This allows for community-driven innovation and improvement. Two popular open-source BI projects are Metabase, a user-friendly data exploration and visualization tool, and Apache Superset, a modern, enterprise-ready BI web application. + +Visit the following resources to learn more: + +- [@opensource@Metabase](https://github.com/metabase/metabase) +- [@opensource@Superset](https://github.com/apache/superset) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/operational-bi@GN6SnI7RXIeW8JeD-qORW.md b/src/data/roadmaps/bi-analyst/content/operational-bi@GN6SnI7RXIeW8JeD-qORW.md index 32f615cb0..3f4dffcea 100644 --- a/src/data/roadmaps/bi-analyst/content/operational-bi@GN6SnI7RXIeW8JeD-qORW.md +++ b/src/data/roadmaps/bi-analyst/content/operational-bi@GN6SnI7RXIeW8JeD-qORW.md @@ -1 +1,3 @@ -# Operational BI \ No newline at end of file +# Operational BI + +Operational planning is the starting point for implementing the actions and goals outlined by tactical planning; aiming to achieve the objectives established in strategic decisions. Operational planning focuses on short-term activities, typically with a 3-6 month horizon. All sectors of the organization are involved in this process, dedicating themselves to monitoring daily activities to ensure execution. \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/operations@dJZqe47kzRqYIG-4AZTlz.md b/src/data/roadmaps/bi-analyst/content/operations@dJZqe47kzRqYIG-4AZTlz.md index 7d7de660e..607fe71e9 100644 --- a/src/data/roadmaps/bi-analyst/content/operations@dJZqe47kzRqYIG-4AZTlz.md +++ b/src/data/roadmaps/bi-analyst/content/operations@dJZqe47kzRqYIG-4AZTlz.md @@ -1 +1,3 @@ -# Operations \ No newline at end of file +# Operations + +Operations encompass all the activities involved in producing and delivering a company's products or services. This includes managing resources, processes, and people to ensure efficiency, quality, and customer satisfaction. It focuses on the day-to-day activities that keep the business running smoothly and meeting its objectives. \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/oracle@uoQS4g-c6QndacUeiaWrq.md b/src/data/roadmaps/bi-analyst/content/oracle@uoQS4g-c6QndacUeiaWrq.md index 1d05ecc39..7bf5ef294 100644 --- a/src/data/roadmaps/bi-analyst/content/oracle@uoQS4g-c6QndacUeiaWrq.md +++ b/src/data/roadmaps/bi-analyst/content/oracle@uoQS4g-c6QndacUeiaWrq.md @@ -1 +1,10 @@ -# Oracle \ No newline at end of file +# Oracle + +Oracle Database is a highly robust, enterprise-grade relational database management system (RDBMS) developed by Oracle Corporation. Known for its scalability, reliability, and comprehensive features, Oracle Database supports complex data management tasks and mission-critical applications. It provides advanced functionalities like SQL querying, transaction management, high availability through clustering, and data warehousing. Oracle's database solutions include support for various data models, such as relational, spatial, and graph, and offer tools for security, performance optimization, and data integration. It is widely used in industries requiring large-scale, secure, and high-performance data processing. + +Visit the following resources to learn more: + +- [@official@Oracle](https://www.oracle.com/database/) +- [@official@Oracle Docs](https://docs.oracle.com/en/database/index.html) +- [@video@Oracle SQL Tutorial for Beginners](https://www.youtube.com/watch?v=ObbNGhcxXJA) +- [@feed@Explore top posts about Oracle](https://app.daily.dev/tags/oracle?ref=roadmapsh) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/other-formats@k80q5FPNiIUdxn5A8R3Hu.md b/src/data/roadmaps/bi-analyst/content/other-formats@k80q5FPNiIUdxn5A8R3Hu.md index 40b24e3cd..4a55a4059 100644 --- a/src/data/roadmaps/bi-analyst/content/other-formats@k80q5FPNiIUdxn5A8R3Hu.md +++ b/src/data/roadmaps/bi-analyst/content/other-formats@k80q5FPNiIUdxn5A8R3Hu.md @@ -1 +1,3 @@ -# Other formats \ No newline at end of file +# Other Data Formats + +Data comes in many forms beyond the common Excel, CSV, JSON, and XML files. These formats are structured ways to store information, but other formats exist to handle different types of data. For example, you might encounter formats like Parquet and Avro, which are optimized for efficient storage and retrieval in big data environments. Databases themselves, like SQL Server or MongoDB, represent structured data formats. Image files (JPEG, PNG), audio files (MP3, WAV), and video files (MP4, MOV) are also data formats, albeit unstructured ones. Understanding the variety of data formats is crucial for accessing and integrating diverse data sources. \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/outliers@OqolfBQRQvwg6PI_t8Mrt.md b/src/data/roadmaps/bi-analyst/content/outliers@OqolfBQRQvwg6PI_t8Mrt.md index a485cb047..96d52f2ae 100644 --- a/src/data/roadmaps/bi-analyst/content/outliers@OqolfBQRQvwg6PI_t8Mrt.md +++ b/src/data/roadmaps/bi-analyst/content/outliers@OqolfBQRQvwg6PI_t8Mrt.md @@ -1 +1,6 @@ -# Outliers \ No newline at end of file +Outliers are unusual or surprising data points that deviate significantly from the rest of the data. While they may be the result of mere variability or error, they will often pull the aggregate data towards them, skewing the results and impeding the accuracy of data analysis. Therefore, identifying and appropriately handling these outliers is crucial to ensure the reliability of subsequent data analysis tasks. + +Visit the following resources to learn more: + +- [@article@Outliers](https://www.mathsisfun.com/data/outliers.html) +- [@article@Outliers in Data Analysis... and how to deal with them!](https://www.youtube.com/watch?v=3lQydBqWYk0&pp=0gcJCfwAo7VqN5tD) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/p-value@rkEdx_mZBoDjMhiluJl7O.md b/src/data/roadmaps/bi-analyst/content/p-value@rkEdx_mZBoDjMhiluJl7O.md index 8abcf2a8b..0c9be905f 100644 --- a/src/data/roadmaps/bi-analyst/content/p-value@rkEdx_mZBoDjMhiluJl7O.md +++ b/src/data/roadmaps/bi-analyst/content/p-value@rkEdx_mZBoDjMhiluJl7O.md @@ -1 +1,9 @@ -# p-value \ No newline at end of file +# P-Value + +The p-value is a number that tells you how likely it is that your data could have occurred under the null hypothesis. It represents the probability of observing a test statistic as extreme as, or more extreme than, the one computed from your sample data, assuming the null hypothesis is true. A small p-value (typically ≤ 0.05) suggests strong evidence against the null hypothesis, so you reject the null hypothesis. A large p-value (> 0.05) suggests weak evidence against the null hypothesis, so you fail to reject the null hypothesis. + +Visit the following resources to learn more: + +- [@article@P-value](https://en.wikipedia.org/wiki/P-value) +- [@article@P-Value: What It Is, How to Calculate It, and Examples](https://www.investopedia.com/terms/p/p-value.asp) +- [@video@What Is A P-Value? - Clearly Explained](https://www.youtube.com/watch?v=ukcFrzt6cHk) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/pandas@25f76eB9-vy3Usta-Pbsi.md b/src/data/roadmaps/bi-analyst/content/pandas@25f76eB9-vy3Usta-Pbsi.md index 7e138e11b..95c8236f6 100644 --- a/src/data/roadmaps/bi-analyst/content/pandas@25f76eB9-vy3Usta-Pbsi.md +++ b/src/data/roadmaps/bi-analyst/content/pandas@25f76eB9-vy3Usta-Pbsi.md @@ -1 +1,9 @@ -# Pandas \ No newline at end of file +# Pandas for Exploratory Data Analysis + +Pandas is a powerful Python library that makes exploring and understanding data much easier. It provides data structures like DataFrames, which are like spreadsheets but much more versatile. With Pandas, you can quickly clean, transform, and analyze your data. It allows you to easily filter rows, select columns, calculate summary statistics (like mean and median), and handle missing values. This makes it a go-to tool for getting a feel for your data and uncovering initial insights before diving into more complex analysis. + +Visit the following resources to learn more: + +- [@official@Pandas Docs](https://pandas.pydata.org/docs/index.html) +- [@article@Python pandas Tutorial: The Ultimate Guide for Beginners](https://www.datacamp.com/tutorial/pandas) +- [@video@Exploratory Data Analysis in Pandas | Python Pandas Tutorials](https://www.youtube.com/watch?v=Liv6eeb1VfE) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/patient-management@LI09SvvUUCQxLZZee_j0n.md b/src/data/roadmaps/bi-analyst/content/patient-management@LI09SvvUUCQxLZZee_j0n.md index 6b1fe35a8..a5a3768bf 100644 --- a/src/data/roadmaps/bi-analyst/content/patient-management@LI09SvvUUCQxLZZee_j0n.md +++ b/src/data/roadmaps/bi-analyst/content/patient-management@LI09SvvUUCQxLZZee_j0n.md @@ -1 +1,7 @@ -# Patient management \ No newline at end of file +# Patient Management + +Data analytics helps healthcare providers manage patients more effectively. By analyzing patient data like medical history, appointments, and treatment outcomes, hospitals and clinics can identify trends and patterns. This information allows them to improve scheduling, reduce wait times, personalize treatment plans, and ultimately provide better care for each patient. + +Visit the following resources to learn more: + +- [@article@Top 8 Use Cases of Healthcare Business Intelligence](https://kms-healthcare.com/blog/healthcare-business-intelligence/) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/performance@y9Fnjnbiqt7WkrhjPITpW.md b/src/data/roadmaps/bi-analyst/content/performance@y9Fnjnbiqt7WkrhjPITpW.md index 55cb80a3a..9b463dbd6 100644 --- a/src/data/roadmaps/bi-analyst/content/performance@y9Fnjnbiqt7WkrhjPITpW.md +++ b/src/data/roadmaps/bi-analyst/content/performance@y9Fnjnbiqt7WkrhjPITpW.md @@ -1 +1,9 @@ -# Performance \ No newline at end of file +# SQL Performance Tuning + +SQL performance tuning involves optimizing SQL queries and database structures to improve the speed and efficiency of data retrieval and manipulation. This includes techniques like indexing, query optimization, and database configuration adjustments to reduce query execution time and minimize resource consumption. The goal is to ensure that SQL queries run quickly and efficiently, providing timely and accurate data for analysis and reporting. + +Visit the following resources to learn more: + +- [@article@SQL Query Optimization: 15 Techniques for Better Performance](https://www.datacamp.com/blog/sql-query-optimization) +- [@article@Performance Tuning SQL Queries](https://mode.com/sql-tutorial/sql-performance-tuning) +- [@official@SQL Roadmap](https://roadmap.sh/sql) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/popular-databases@gJBaVERU3prru-qRksxN4.md b/src/data/roadmaps/bi-analyst/content/popular-databases@gJBaVERU3prru-qRksxN4.md index 56a60ff01..1f41059ce 100644 --- a/src/data/roadmaps/bi-analyst/content/popular-databases@gJBaVERU3prru-qRksxN4.md +++ b/src/data/roadmaps/bi-analyst/content/popular-databases@gJBaVERU3prru-qRksxN4.md @@ -1 +1,3 @@ -# Popular Databases \ No newline at end of file +# Popular Databases + +Relational databases are a common way to store and organize data in tables with rows and columns. They use relationships between these tables to efficiently manage information. Some popular examples include MySQL, a widely used open-source database; PostgreSQL, known for its robustness and adherence to standards; SQLite, a lightweight database often embedded in applications; and Oracle, a commercial database known for its scalability and features. \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/population--sample@7VDxA9bQ1P1fym4eQVKkN.md b/src/data/roadmaps/bi-analyst/content/population--sample@7VDxA9bQ1P1fym4eQVKkN.md index a2dc00cab..c0d7cfcb9 100644 --- a/src/data/roadmaps/bi-analyst/content/population--sample@7VDxA9bQ1P1fym4eQVKkN.md +++ b/src/data/roadmaps/bi-analyst/content/population--sample@7VDxA9bQ1P1fym4eQVKkN.md @@ -1 +1,8 @@ -# Population & Sample \ No newline at end of file +# Population & Sample + +In statistics, a population refers to the entire group you want to draw conclusions about, while a sample is a smaller, manageable subset of that population that you actually collect data from. Because it's often impractical or impossible to study an entire population, we use samples to make inferences or generalizations about the larger group. The goal is to ensure the sample is representative of the population so that the conclusions drawn from the sample data are accurate and reliable for the entire population. + +Visit the following resources to learn more: + +- [@article@Population vs. Sample | Definitions, Differences & Examples](https://www.scribbr.com/methodology/population-vs-sample/) +- [@article@Difference Between Population And Sample](https://www.simplilearn.com/tutorials/machine-learning-tutorial/population-vs-sample) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/portfolio-presentation@qsCWo1CmR4mvy7E7qlPv5.md b/src/data/roadmaps/bi-analyst/content/portfolio-presentation@qsCWo1CmR4mvy7E7qlPv5.md index e83056529..903e30c7f 100644 --- a/src/data/roadmaps/bi-analyst/content/portfolio-presentation@qsCWo1CmR4mvy7E7qlPv5.md +++ b/src/data/roadmaps/bi-analyst/content/portfolio-presentation@qsCWo1CmR4mvy7E7qlPv5.md @@ -1 +1,3 @@ -# Portfolio presentation \ No newline at end of file +# Portfolio Presentation + +A portfolio presentation is a structured way to showcase your skills and experience to potential employers. It involves selecting relevant projects, highlighting your contributions and the impact of your work, and presenting them in a clear and compelling manner. The goal is to demonstrate your abilities and how you can add value to their organization. \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/postgresql@nhl9FM79femgqENNR0HbE.md b/src/data/roadmaps/bi-analyst/content/postgresql@nhl9FM79femgqENNR0HbE.md index 9892a29dc..e496674db 100644 --- a/src/data/roadmaps/bi-analyst/content/postgresql@nhl9FM79femgqENNR0HbE.md +++ b/src/data/roadmaps/bi-analyst/content/postgresql@nhl9FM79femgqENNR0HbE.md @@ -1 +1,12 @@ -# PostgreSQL \ No newline at end of file +# PostgreSQL + +PostgreSQL is an advanced, open-source relational database management system (RDBMS) known for its robustness, extensibility, and standards compliance. It supports a wide range of data types and advanced features, including complex queries, foreign keys, and full-text search. PostgreSQL is highly extensible, allowing users to define custom data types, operators, and functions. It supports ACID (Atomicity, Consistency, Isolation, Durability) properties for reliable transaction processing and offers strong support for concurrency and data integrity. Its capabilities make it suitable for various applications, from simple web apps to large-scale data warehousing and analytics solutions. + +Visit the following resources to learn more: + +- [@roadmap@Visit Dedicated PostgreSQL DBA Roadmap](https://roadmap.sh/postgresql-dba) +- [@official@Official Website](https://www.postgresql.org/) +- [@article@Learn PostgreSQL - Full Tutorial for Beginners](ttps://www.postgresqltutorial.com/) +- [@video@ostgres tutorial for Beginners](https://www.youtube.com/watch?v=SpfIwlAYaKk) +- [@feed@Explore top posts about PostgreSQL](https://app.daily.dev/tags/postgresql?ref=roadmapsh) +- [@course@PostgreSQL: Become an SQL developer](https://www.simplilearn.com/free-postgresql-course-skillup) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/power-bi@eqGsO6ZGk2jdG0z9-cHzz.md b/src/data/roadmaps/bi-analyst/content/power-bi@eqGsO6ZGk2jdG0z9-cHzz.md index 58f8a4abf..42a4f7317 100644 --- a/src/data/roadmaps/bi-analyst/content/power-bi@eqGsO6ZGk2jdG0z9-cHzz.md +++ b/src/data/roadmaps/bi-analyst/content/power-bi@eqGsO6ZGk2jdG0z9-cHzz.md @@ -1 +1,9 @@ -# Power BI \ No newline at end of file +# Power BI + +PowerBI, an interactive data visualization and business analytics tool developed by Microsoft, plays a crucial role in the field of a data analyst's work. It helps data analysts to convert raw data into meaningful insights through it's easy-to-use dashboards and reports function. This tool provides a unified view of business data, allowing analysts to track and visualize key performance metrics and make better-informed business decisions. With PowerBI, data analysts also have the ability to manipulate and produce visualizations of large data sets that can be shared across an organization, making complex statistical information more digestible. + +Visit the following resources to learn more: + +- [@official@Power BI](https://www.microsoft.com/en-us/power-platform/products/power-bi) +- [@video@Power BI for beginners](https://www.youtube.com/watch?v=NNSHu0rkew8) +- [@video@Power BI Full Course for Free in 20 Hours](https://www.youtube.com/watch?v=cyWVzAQF9YU) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/predictive-analysis@4zpVE3R0lLyWpHePdBVpl.md b/src/data/roadmaps/bi-analyst/content/predictive-analysis@4zpVE3R0lLyWpHePdBVpl.md index e2e062081..0b8a80fd3 100644 --- a/src/data/roadmaps/bi-analyst/content/predictive-analysis@4zpVE3R0lLyWpHePdBVpl.md +++ b/src/data/roadmaps/bi-analyst/content/predictive-analysis@4zpVE3R0lLyWpHePdBVpl.md @@ -1 +1,8 @@ -# Predictive Analysis \ No newline at end of file +# Predictive analysis + +Predictive analysis is a crucial type of data analytics that any competent data analyst should comprehend. It refers to the practice of extracting information from existing data sets in order to determine patterns and forecast future outcomes and trends. Data analysts apply statistical algorithms, machine learning techniques, and artificial intelligence to the data to anticipate future results. Predictive analysis enables organizations to be proactive, forward-thinking, and strategic by providing them valuable insights on future occurrences. It's a powerful tool that gives companies a significant competitive edge by enabling risk management, opportunity identification, and strategic decision-making. + +Visit the following resources to learn more: + +- [@article@What is Predictive Analytics? - Google](https://cloud.google.com/learn/what-is-predictive-analytics) +- [@video@hat is Predictive Analytics?](https://www.youtube.com/watch?v=cVibCHRSxB0) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/predictive-maintenance@yimCxOdNtyGcbd6ZxHsBQ.md b/src/data/roadmaps/bi-analyst/content/predictive-maintenance@yimCxOdNtyGcbd6ZxHsBQ.md index b3ffc9f2b..cb4d4c854 100644 --- a/src/data/roadmaps/bi-analyst/content/predictive-maintenance@yimCxOdNtyGcbd6ZxHsBQ.md +++ b/src/data/roadmaps/bi-analyst/content/predictive-maintenance@yimCxOdNtyGcbd6ZxHsBQ.md @@ -1 +1,8 @@ -# Predictive Maintenance \ No newline at end of file +# Predictive Maintenance + +Predictive maintenance uses data analysis and machine learning to forecast when equipment failures are likely to occur. This allows manufacturers to schedule maintenance proactively, minimizing downtime and reducing costs associated with unexpected breakdowns. By analyzing sensor data, historical maintenance records, and other relevant information, predictive maintenance models can identify patterns and anomalies that indicate potential problems before they lead to significant disruptions. + +Visit the following resources to learn more: + +- [@article@What is Predictive Maintenance?](https://www.ibm.com/think/topics/predictive-maintenance) +- [@video@Predictive Maintenance Explained](https://www.youtube.com/watch?v=2_o1SDy6__U) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/prescriptive-analysis@NnbtaO2MiqsHeJ-ds0Q5m.md b/src/data/roadmaps/bi-analyst/content/prescriptive-analysis@NnbtaO2MiqsHeJ-ds0Q5m.md index 8b1553c05..09f9c8078 100644 --- a/src/data/roadmaps/bi-analyst/content/prescriptive-analysis@NnbtaO2MiqsHeJ-ds0Q5m.md +++ b/src/data/roadmaps/bi-analyst/content/prescriptive-analysis@NnbtaO2MiqsHeJ-ds0Q5m.md @@ -1 +1,8 @@ -# Prescriptive Analysis \ No newline at end of file +# Prescriptive Analytics + +Prescriptive analytics, a crucial type of data analytics, is essential for making data-driven decisions in business and organizational contexts. As a data analyst, the goal of prescriptive analytics is to recommend various actions using predictions on the basis of known parameters to help decision makers understand likely outcomes. Prescriptive analytics employs a blend of techniques and tools such as algorithms, machine learning, computational modelling procedures, and decision-tree structures to enable automated decision making. Therefore, prescriptive analytics not only anticipates what will happen and when it will happen, but also explains why it will happen, contributing to the significance of a data analyst’s role in an organization. + +Visit the following resources to learn more: + +- [@article@What is Prescriptive Analysis?](https://www.investopedia.com/terms/p/prescriptive-analytics.asp) +- [@video@Examples of Prescriptive Analysis](https://www.youtube.com/watch?v=NOo8Nc9zG20) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/presentation-design@9G-pI5NsRCq4p0FLfaMR_.md b/src/data/roadmaps/bi-analyst/content/presentation-design@9G-pI5NsRCq4p0FLfaMR_.md index 198cb5801..ff386fb2e 100644 --- a/src/data/roadmaps/bi-analyst/content/presentation-design@9G-pI5NsRCq4p0FLfaMR_.md +++ b/src/data/roadmaps/bi-analyst/content/presentation-design@9G-pI5NsRCq4p0FLfaMR_.md @@ -1 +1,7 @@ -# Presentation Design \ No newline at end of file +# Presentation Design + +Presentation design involves creating visually appealing and engaging slides or materials to effectively communicate information to an audience. It encompasses elements like layout, color schemes, typography, imagery, and data visualization to ensure the message is clear, concise, and memorable. A well-designed presentation helps to capture attention, maintain interest, and facilitate understanding of the key insights being presented. + +Visit the following resources to learn more: + +- [@video@Visual storytelling 101: elevating presentations with data visualization](https://www.youtube.com/watch?v=NXx0xQn7OXI) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/privacy@fuxGZx3WGjP2TzzVV29ux.md b/src/data/roadmaps/bi-analyst/content/privacy@fuxGZx3WGjP2TzzVV29ux.md index e18bbf1e8..96544d235 100644 --- a/src/data/roadmaps/bi-analyst/content/privacy@fuxGZx3WGjP2TzzVV29ux.md +++ b/src/data/roadmaps/bi-analyst/content/privacy@fuxGZx3WGjP2TzzVV29ux.md @@ -1 +1,7 @@ -# Privacy \ No newline at end of file +# Privacy + +Privacy refers to the right of individuals to control how their personal information is collected, used, and shared. It encompasses various aspects, including data security, confidentiality, and compliance with regulations like GDPR and CCPA. Protecting privacy involves implementing policies and procedures to safeguard sensitive data and ensuring transparency in data handling practices. + +Visit the following resources to learn more: + +- [@article@What Is Data Privacy?](https://www.ibm.com/think/topics/data-privacy) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/production-efficiency@L50rpcgGjsQU3S0zRn6xh.md b/src/data/roadmaps/bi-analyst/content/production-efficiency@L50rpcgGjsQU3S0zRn6xh.md index a6b39cefd..eff59dd40 100644 --- a/src/data/roadmaps/bi-analyst/content/production-efficiency@L50rpcgGjsQU3S0zRn6xh.md +++ b/src/data/roadmaps/bi-analyst/content/production-efficiency@L50rpcgGjsQU3S0zRn6xh.md @@ -1 +1,3 @@ -# Production Efficiency \ No newline at end of file +# Production Efficiency + +Production efficiency measures how well a manufacturing process converts inputs (like raw materials, labor, and energy) into outputs (finished goods). It focuses on minimizing waste, optimizing resource utilization, and streamlining workflows to produce the maximum possible output with the least amount of input. Analyzing production efficiency involves tracking key performance indicators (KPIs) such as throughput, cycle time, and defect rates to identify areas for improvement and ultimately reduce costs and increase profitability. \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/professional-development@tUxwKTml2Go8zR9tR3cjn.md b/src/data/roadmaps/bi-analyst/content/professional-development@tUxwKTml2Go8zR9tR3cjn.md index dd433ae25..71e3de4fa 100644 --- a/src/data/roadmaps/bi-analyst/content/professional-development@tUxwKTml2Go8zR9tR3cjn.md +++ b/src/data/roadmaps/bi-analyst/content/professional-development@tUxwKTml2Go8zR9tR3cjn.md @@ -1 +1,3 @@ -# Professional Development \ No newline at end of file +# Professional Development + +Professional development encompasses activities that enhance an individual's skills, knowledge, and expertise within their field. It involves continuous learning and growth through various avenues such as training courses, certifications, conferences, mentorship, and self-directed study. The goal is to stay current with industry trends, improve performance, and advance one's career. \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/programming-languages@KSxjcWV6C325kZITzAhWs.md b/src/data/roadmaps/bi-analyst/content/programming-languages@KSxjcWV6C325kZITzAhWs.md index 9e0e14267..6b5ba13e4 100644 --- a/src/data/roadmaps/bi-analyst/content/programming-languages@KSxjcWV6C325kZITzAhWs.md +++ b/src/data/roadmaps/bi-analyst/content/programming-languages@KSxjcWV6C325kZITzAhWs.md @@ -1 +1,3 @@ -# Programming Languages \ No newline at end of file +# Programming Languages for BI Analysts + +Programming languages are sets of instructions that tell computers what to do. For BI Analysts, learning a programming language unlocks powerful capabilities beyond standard BI tools. It allows you to automate tasks, clean and transform data in complex ways, build custom visualizations, and integrate different data sources. By learning a programming language, BI Analysts can solve more complex problems and gain deeper insights from data. \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/project-management@r8NoX426-ngu6ZQZe06oK.md b/src/data/roadmaps/bi-analyst/content/project-management@r8NoX426-ngu6ZQZe06oK.md index 9ef7e05d9..2c863a214 100644 --- a/src/data/roadmaps/bi-analyst/content/project-management@r8NoX426-ngu6ZQZe06oK.md +++ b/src/data/roadmaps/bi-analyst/content/project-management@r8NoX426-ngu6ZQZe06oK.md @@ -1 +1,3 @@ -# Project Management \ No newline at end of file +# Project Management + +Project management involves planning, organizing, and overseeing the completion of specific goals. It encompasses defining project objectives, creating timelines, allocating resources, and managing risks to ensure projects are delivered on time, within budget, and to the required quality. Effective project management relies on clear communication, collaboration, and problem-solving skills to navigate challenges and keep stakeholders aligned. \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/providers-aws-gcp-azure@Z4pAe4FpnCkUJt8RuOhC6.md b/src/data/roadmaps/bi-analyst/content/providers-aws-gcp-azure@Z4pAe4FpnCkUJt8RuOhC6.md index c5ab4d1dd..84bb55df0 100644 --- a/src/data/roadmaps/bi-analyst/content/providers-aws-gcp-azure@Z4pAe4FpnCkUJt8RuOhC6.md +++ b/src/data/roadmaps/bi-analyst/content/providers-aws-gcp-azure@Z4pAe4FpnCkUJt8RuOhC6.md @@ -1 +1,10 @@ -# Providers: AWS, GCP, Azure \ No newline at end of file +# Cloud Providers: AWS, GCP, and Azure + +Amazon Web Services (AWS), Google Cloud Platform (GCP), and Microsoft Azure are the leading cloud providers, offering a wide range of services. These services include computing power, data storage, networking, databases, analytics, machine learning, and more, all accessible over the internet. They allow businesses to avoid the upfront costs and complexities of owning and managing their own IT infrastructure, providing scalable and on-demand resources. + +Visit the following resources to learn more: + +- [@official@Amazon Web Services](https://aws.amazon.com/) +- [@article@Microsoft Azure](https://azure.microsoft.com/) +- [@article@Google Cloud](https://cloud.google.com/) +- [@video@The Basics You Need to Know about AWS, Azure, and Google Cloud](https://www.youtube.com/watch?v=wFsOjHgvUfM) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/public-health@Cydlrtg_FClBUkjezqGie.md b/src/data/roadmaps/bi-analyst/content/public-health@Cydlrtg_FClBUkjezqGie.md index 7a296fc97..696e04134 100644 --- a/src/data/roadmaps/bi-analyst/content/public-health@Cydlrtg_FClBUkjezqGie.md +++ b/src/data/roadmaps/bi-analyst/content/public-health@Cydlrtg_FClBUkjezqGie.md @@ -1 +1,3 @@ -# Public Health \ No newline at end of file +# Public Health Data Analytics + +Data analytics in public health uses information to understand and tackle health issues affecting large groups of people. During events like pandemics, analyzing data on disease spread, patient demographics, and resource availability helps identify hotspots, predict future outbreaks, and optimize the distribution of medical supplies. This allows public health officials to make informed decisions, implement targeted interventions, and ultimately improve health outcomes for the population. \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/python@vQQSYPpcGO7ri0RFSWi0h.md b/src/data/roadmaps/bi-analyst/content/python@vQQSYPpcGO7ri0RFSWi0h.md index 92106a828..56d0ae617 100644 --- a/src/data/roadmaps/bi-analyst/content/python@vQQSYPpcGO7ri0RFSWi0h.md +++ b/src/data/roadmaps/bi-analyst/content/python@vQQSYPpcGO7ri0RFSWi0h.md @@ -1 +1,11 @@ -# Python \ No newline at end of file +# Python for BI Analysts + +Python is a versatile and widely-used programming language known for its readability and extensive libraries. Learning Python as a BI analyst is crucial because it allows you to automate tasks like data cleaning and transformation, perform advanced statistical analysis beyond the capabilities of standard BI tools, and create custom visualizations. It empowers you to work with larger and more complex datasets, ultimately leading to deeper insights and more effective data-driven decision-making. + +Visit the following resources to learn more: + +- [@roadmap@Visit Dedicated Python Roadmap](https://roadmap.sh/python) +- [@official@Python](https://www.python.org/) +- [@article@Real Python](https://realpython.com/) +- [@video@Ultimate Data Analyst Bootcamp [24 Hours!]](https://www.youtube.com/watch?v=wQQR60KtnFY) +- [@book@Python for Data Analysis](https://datapot.vn/wp-content/uploads/2023/12/datapot.vn-Python-for-Data-Analysis.pdf?srsltid=AfmBOopeeuwebcpwD9crBjnMo3wchpUtvkz-g1T2Phi7FFyjkx7l5t9e) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/qlik@GoMIAQwusbT7fqJ-VnCrq.md b/src/data/roadmaps/bi-analyst/content/qlik@GoMIAQwusbT7fqJ-VnCrq.md index ee79f5290..3494efc04 100644 --- a/src/data/roadmaps/bi-analyst/content/qlik@GoMIAQwusbT7fqJ-VnCrq.md +++ b/src/data/roadmaps/bi-analyst/content/qlik@GoMIAQwusbT7fqJ-VnCrq.md @@ -1 +1,8 @@ -# Qlik \ No newline at end of file +# Qlik + +Qlik is a data analytics platform that allows users to explore data, discover insights, and make data-driven decisions. It uses associative technology, which enables users to explore relationships within data regardless of where it's stored. Qlik offers self-service analytics, data visualization, and data integration capabilities, empowering users to analyze data without relying solely on IT or data science teams. + +Visit the following resources to learn more: + +- [@official@Qlik](https://www.qlik.com/) +- [@video@Qlik Sense Tutorial: 3.5 Hours of Beginner to Advanced Qlik Sense Training](https://www.youtube.com/watch?v=ny8d2XlTWsQ) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/quality-control@Xe9zK8xhkkr4fsh3HOzAY.md b/src/data/roadmaps/bi-analyst/content/quality-control@Xe9zK8xhkkr4fsh3HOzAY.md index e9b7babf5..e7cffb945 100644 --- a/src/data/roadmaps/bi-analyst/content/quality-control@Xe9zK8xhkkr4fsh3HOzAY.md +++ b/src/data/roadmaps/bi-analyst/content/quality-control@Xe9zK8xhkkr4fsh3HOzAY.md @@ -1 +1,7 @@ -# Quality Control \ No newline at end of file +# Quality Control + +Quality control in manufacturing involves systematically monitoring and evaluating products or processes to ensure they meet predefined standards and specifications. This includes identifying defects, analyzing their root causes, and implementing corrective actions to improve product quality and process efficiency. The goal is to minimize errors, reduce waste, and consistently deliver high-quality products to customers. + +Visit the following resources to learn more: + +- [@article@Quality Control in Manufacturing: Methods, Best Practices, and Implementation](https://www.starrapid.com/blog/quality-control-in-manufacturing/) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/r@0OTmTRHlR3ImNU0zyLt8G.md b/src/data/roadmaps/bi-analyst/content/r@0OTmTRHlR3ImNU0zyLt8G.md index 7a53bd159..792d94c9f 100644 --- a/src/data/roadmaps/bi-analyst/content/r@0OTmTRHlR3ImNU0zyLt8G.md +++ b/src/data/roadmaps/bi-analyst/content/r@0OTmTRHlR3ImNU0zyLt8G.md @@ -1 +1,10 @@ -# R \ No newline at end of file +# R Programming for Business Intelligence + +R is a programming language and free software environment widely used for statistical computing and graphics. For BI analysts, R is valuable because it allows for advanced data analysis, statistical modeling, and the creation of custom visualizations beyond the capabilities of many standard BI tools. It empowers analysts to uncover deeper insights, build predictive models, and communicate findings effectively. + +Visit the following resources to learn more: + +- [@official@R](https://www.r-project.org/) +- [@book@R for Data Science](https://r4ds.hadley.nz/) +- [@article@What is R? - An Introduction to The Statistical Computing Powerhouse](https://www.datacamp.com/blog/all-about-r) +- [@video@R Programming For Beginners](https://www.youtube.com/watch?v=KlsYCECWEWE&list=PLEiEAq2VkUUKAw0aAJ1W4jpZ1q9LpX4yG) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/range@jll2iRbjdx7iiNwY13KYD.md b/src/data/roadmaps/bi-analyst/content/range@jll2iRbjdx7iiNwY13KYD.md index 20259f08c..4e49685d4 100644 --- a/src/data/roadmaps/bi-analyst/content/range@jll2iRbjdx7iiNwY13KYD.md +++ b/src/data/roadmaps/bi-analyst/content/range@jll2iRbjdx7iiNwY13KYD.md @@ -1 +1,7 @@ -# Range \ No newline at end of file +# Range + +The range is a simple measure of dispersion that indicates the spread of data in a dataset. It's calculated by subtracting the smallest value from the largest value. The range provides a quick and easy way to understand the variability within a dataset, showing the total distance covered by the data points. + +Visit the following resources to learn more: + +- [@article@How to Find the Range of a Data Set](https://www.scribbr.co.uk/stats/range-statistics/) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/regression-analysis@m9ejACzRBJza0v-fpdfkn.md b/src/data/roadmaps/bi-analyst/content/regression-analysis@m9ejACzRBJza0v-fpdfkn.md index c3aa4b28f..dd82f24e8 100644 --- a/src/data/roadmaps/bi-analyst/content/regression-analysis@m9ejACzRBJza0v-fpdfkn.md +++ b/src/data/roadmaps/bi-analyst/content/regression-analysis@m9ejACzRBJza0v-fpdfkn.md @@ -1 +1,9 @@ -# Regression Analysis \ No newline at end of file +# Regression Analysis + +Regression analysis is a form of predictive modelling technique which investigates the relationship between dependent and independent variables. It is used for forecast, time series modelling and finding the causal effect relationship between variables. In essence, Regression techniques are used by BI analysts to predict a continuous outcome variable (dependent variable) based on one or more predictor variables (independent variables). The main goal is to understand how the typical value of the dependent variable changes when any one of the independent variables is varied, while the other independent variables are held fixed. + +Visit the following resources to learn more: + +- [@article@Regression: Definition, Analysis, Calculation, and Example](https://www.investopedia.com/terms/r/regression.asp) +- [@article@A Refresher on Regression Analysis - Harvard](https://hbr.org/2015/11/a-refresher-on-regression-analysis) +- [@course@Intro to Inferential Statistics](https://www.udacity.com/course/intro-to-inferential-statistics--ud201) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/reinforcement-learning@KFONHuJNnCuSOH7-8Ndvm.md b/src/data/roadmaps/bi-analyst/content/reinforcement-learning@KFONHuJNnCuSOH7-8Ndvm.md index 998d9bd63..87ac80d2b 100644 --- a/src/data/roadmaps/bi-analyst/content/reinforcement-learning@KFONHuJNnCuSOH7-8Ndvm.md +++ b/src/data/roadmaps/bi-analyst/content/reinforcement-learning@KFONHuJNnCuSOH7-8Ndvm.md @@ -1 +1,10 @@ -# Reinforcement Learning \ No newline at end of file +# Reinforcement Learning + +Reinforcement learning is a type of machine learning where an agent learns to make decisions in an environment to maximize a cumulative reward. It involves the agent taking actions, receiving feedback in the form of rewards or penalties, and adjusting its strategy to improve its performance over time. Unlike supervised learning, it doesn't rely on labeled data but rather learns through trial and error. + +Visit the following resources to learn more: + +- [@article@What is reinforcement learning?](https://online.york.ac.uk/resources/what-is-reinforcement-learning/) +- [@article@Resources to Learn Reinforcement Learning](https://towardsdatascience.com/best-free-courses-and-resources-to-learn-reinforcement-learning-ed6633608cb2/) +- [@course@Deep Reinforcement Learning Course by HuggingFace](https://huggingface.co/learn/deep-rl-course/unit0/introduction) +- [@video@Reinforcement Learning in 3 Hours | Full Course using Python](https://www.youtube.com/watch?v=Mut_u40Sqz4) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/relevance@UhcniUDKmi7KNuXlolf5O.md b/src/data/roadmaps/bi-analyst/content/relevance@UhcniUDKmi7KNuXlolf5O.md index c895d7ab0..d50ce931b 100644 --- a/src/data/roadmaps/bi-analyst/content/relevance@UhcniUDKmi7KNuXlolf5O.md +++ b/src/data/roadmaps/bi-analyst/content/relevance@UhcniUDKmi7KNuXlolf5O.md @@ -1 +1,3 @@ -# Relevance \ No newline at end of file +# Relevance + +Relevance, in the context of data quality, refers to the degree to which data is useful and applicable for its intended purpose. Data is considered relevant if it directly addresses the needs of the analysis or decision-making process it's being used for. Irrelevant data can lead to inaccurate insights, wasted resources, and ultimately, poor business outcomes. \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/responsibilities@Q-GmBJiRdBS_xLeOjef2R.md b/src/data/roadmaps/bi-analyst/content/responsibilities@Q-GmBJiRdBS_xLeOjef2R.md index 526ef68b1..74bfc3081 100644 --- a/src/data/roadmaps/bi-analyst/content/responsibilities@Q-GmBJiRdBS_xLeOjef2R.md +++ b/src/data/roadmaps/bi-analyst/content/responsibilities@Q-GmBJiRdBS_xLeOjef2R.md @@ -1,3 +1,15 @@ -# Responsibilities of a BI Analyst +# BI Analyst Responsibilities -A BI Analyst is responsible for analyzing data to identify trends, patterns, and insights that can help organizations make better business decisions. This involves collecting data from various sources, cleaning and transforming it into a usable format, and then using statistical techniques and data visualization tools to interpret the data and communicate findings to stakeholders. Ultimately, the goal is to provide actionable recommendations that improve performance, efficiency, and profitability. \ No newline at end of file +As a BI Analyst, you're the bridge between raw data and actionable insights. You transform complex information into clear, understandable reports and dashboards that drive strategic decision-making. Your work empowers stakeholders to identify trends, optimize performance, and achieve business goals. + +Here are 5 main responsibilities of a BI Analyst: + +* **Data Collection & Cleaning:** Gathering data from various sources and ensuring its accuracy and consistency. +* **Data Analysis & Modeling:** Analyzing data to identify trends, patterns, and insights, and creating data models for reporting. +* **Report & Dashboard Development:** Designing and building interactive dashboards and reports to visualize data and communicate findings. +* **Stakeholder Communication:** Presenting findings and recommendations to stakeholders in a clear and concise manner. +* **Performance Monitoring:** Tracking key performance indicators (KPIs) and identifying areas for improvement. + +Visit the following resources to learn more: + +- [@article@So What Do You Actually Do As A BI Analyst?](https://www.youtube.com/watch?v=TaRuzC8RSZU) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/resume-optimization@m9EwcekZ_l0XHiKeQ8emr.md b/src/data/roadmaps/bi-analyst/content/resume-optimization@m9EwcekZ_l0XHiKeQ8emr.md index 0a58a3afb..926b741d0 100644 --- a/src/data/roadmaps/bi-analyst/content/resume-optimization@m9EwcekZ_l0XHiKeQ8emr.md +++ b/src/data/roadmaps/bi-analyst/content/resume-optimization@m9EwcekZ_l0XHiKeQ8emr.md @@ -1 +1,7 @@ -# Resume optimization \ No newline at end of file +# Resume Optimization + +Resume optimization is the process of refining your resume to make it more appealing to potential employers. This involves tailoring your resume to match specific job descriptions, using relevant keywords, highlighting your accomplishments with quantifiable results, and ensuring a clear and concise format. You can optimize your resume by carefully reviewing job postings, identifying key skills and experiences, and then rewriting your resume to emphasize those areas. Also, new AI-powered tools are emerging to help you optimize your resume. + +Visit the following resources to learn more: + +- [@article@Top 10 AI Tools for Resumes and Job Applications](https://www.quantumanalyticsco.org/blog/top-10-ai-tools-for-resumes-and-job-applications) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/retail--e-commerce@7LbhfkmS7oFoSF1k5ZR1U.md b/src/data/roadmaps/bi-analyst/content/retail--e-commerce@7LbhfkmS7oFoSF1k5ZR1U.md index a9206c427..fd01286a5 100644 --- a/src/data/roadmaps/bi-analyst/content/retail--e-commerce@7LbhfkmS7oFoSF1k5ZR1U.md +++ b/src/data/roadmaps/bi-analyst/content/retail--e-commerce@7LbhfkmS7oFoSF1k5ZR1U.md @@ -1 +1,3 @@ -# Retail & E-commerce \ No newline at end of file +# Retail & E-commerce + +Business intelligence in retail and e-commerce helps companies understand their sales trends, customer behavior, and operational efficiency. By analyzing data from various sources like point-of-sale systems, website analytics, and customer databases, retailers can identify top-selling products, optimize pricing strategies, personalize marketing campaigns, and improve inventory management. This data-driven approach enables them to make informed decisions, enhance customer experiences, and ultimately increase profitability. \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/risk-analytics@JHGV0V78GXubiSY9P3nTw.md b/src/data/roadmaps/bi-analyst/content/risk-analytics@JHGV0V78GXubiSY9P3nTw.md index 723705236..4a2be269d 100644 --- a/src/data/roadmaps/bi-analyst/content/risk-analytics@JHGV0V78GXubiSY9P3nTw.md +++ b/src/data/roadmaps/bi-analyst/content/risk-analytics@JHGV0V78GXubiSY9P3nTw.md @@ -1 +1,8 @@ -# Risk Analytics \ No newline at end of file +# Risk Analytics + +Risk analytics involves identifying, assessing, and mitigating potential risks that could impact an organization's financial stability and overall performance. It uses data analysis techniques to understand the likelihood and potential consequences of various risks, such as market volatility, credit defaults, and operational failures. The goal is to provide insights that enable informed decision-making and proactive risk management strategies. + +Visit the following resources to learn more: + +- [@article@What are financial risk analytics?](http://stripe.com/en-es/resources/more/what-are-financial-risk-analytics-what-businesses-need-to-know) +- [@article@Risk Analysis: Definition, Types, Limitations, and Examples](https://www.investopedia.com/terms/r/risk-analysis.asp) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/salary-negotiation-strategies@k3F9Tdqo3XYgMLOKGjpxA.md b/src/data/roadmaps/bi-analyst/content/salary-negotiation-strategies@k3F9Tdqo3XYgMLOKGjpxA.md index 2b854cb0c..fd4de2156 100644 --- a/src/data/roadmaps/bi-analyst/content/salary-negotiation-strategies@k3F9Tdqo3XYgMLOKGjpxA.md +++ b/src/data/roadmaps/bi-analyst/content/salary-negotiation-strategies@k3F9Tdqo3XYgMLOKGjpxA.md @@ -1 +1,7 @@ -# Salary negotiation strategies \ No newline at end of file +# Salary Negotiation Strategies + +Salary negotiation strategies involve preparing for and engaging in discussions with potential employers to secure the best possible compensation package. This includes researching industry benchmarks, understanding your worth, practicing your negotiation skills, and knowing when to compromise or walk away. The goal is to confidently advocate for your value and achieve a salary that reflects your skills and experience. + +Visit the following resources to learn more: + +- [@article@15 Rules for Negotiating a Job Offer](https://hbr.org/2014/04/15-rules-for-negotiating-a-job-offer) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/sales-performance@VPu8vn7-baZQ5ORJ6ViW0.md b/src/data/roadmaps/bi-analyst/content/sales-performance@VPu8vn7-baZQ5ORJ6ViW0.md index 533175fac..58d1fff9b 100644 --- a/src/data/roadmaps/bi-analyst/content/sales-performance@VPu8vn7-baZQ5ORJ6ViW0.md +++ b/src/data/roadmaps/bi-analyst/content/sales-performance@VPu8vn7-baZQ5ORJ6ViW0.md @@ -1 +1,3 @@ -# Sales Performance \ No newline at end of file +# Sales Performance + +Sales performance refers to how well a company or individual is doing in terms of generating revenue through sales activities. It involves tracking, analyzing, and improving various metrics like sales volume, revenue growth, conversion rates, and customer acquisition cost to understand what's working and what's not in the sales process. This understanding helps businesses make informed decisions to optimize their sales strategies and achieve their revenue targets. \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/scatterplot@hCSZo7jT9arBLUbtCVFfD.md b/src/data/roadmaps/bi-analyst/content/scatterplot@hCSZo7jT9arBLUbtCVFfD.md index 2ca26873a..5a9cecc60 100644 --- a/src/data/roadmaps/bi-analyst/content/scatterplot@hCSZo7jT9arBLUbtCVFfD.md +++ b/src/data/roadmaps/bi-analyst/content/scatterplot@hCSZo7jT9arBLUbtCVFfD.md @@ -1 +1,3 @@ -# Scatterplot \ No newline at end of file +# Scatterplot + +A scatterplot is a type of data visualization that uses dots to represent values for two different variables. Each dot's position on the horizontal and vertical axes indicates the values for an individual data point. Scatterplots are primarily used to observe and display the relationship or correlation between these two variables, revealing patterns, clusters, and outliers in the data. \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/seasonality@moWrEfuKE06QwbznsH3V-.md b/src/data/roadmaps/bi-analyst/content/seasonality@moWrEfuKE06QwbznsH3V-.md index cbbf14d55..0ef370579 100644 --- a/src/data/roadmaps/bi-analyst/content/seasonality@moWrEfuKE06QwbznsH3V-.md +++ b/src/data/roadmaps/bi-analyst/content/seasonality@moWrEfuKE06QwbznsH3V-.md @@ -1 +1,7 @@ -# Seasonality \ No newline at end of file +# Seasonality + +Seasonality refers to predictable, recurring patterns within a time series dataset that occur over a fixed period. These patterns repeat regularly, such as daily, weekly, monthly, or yearly. Identifying and understanding seasonality is crucial for accurate forecasting and analysis, as it allows you to account for these repeating fluctuations and make more informed predictions about future trends. + +Visit the following resources to learn more: + +- [@video@Complete Time Series Analysis and Forecasting with Python](https://www.youtube.com/watch?v=eKiXtGzEjos) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/semistructured@qHcRrxenhogymMQ6EPiMa.md b/src/data/roadmaps/bi-analyst/content/semistructured@qHcRrxenhogymMQ6EPiMa.md index 7f3562c06..c15d3e942 100644 --- a/src/data/roadmaps/bi-analyst/content/semistructured@qHcRrxenhogymMQ6EPiMa.md +++ b/src/data/roadmaps/bi-analyst/content/semistructured@qHcRrxenhogymMQ6EPiMa.md @@ -1 +1,3 @@ -# Semistructured \ No newline at end of file +# Semistructured Data + +Semistructured data doesn't conform to the rigid structure of a relational database but still has some organizational properties, like tags or markers, that separate data elements and enforce hierarchies of records and fields within the data. It's not raw data, but it also doesn't fit neatly into tables with rows and columns. Examples include JSON and XML files, where data is organized using tags and attributes, making it easier to parse and understand than completely unstructured data. \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/skewness@X0DBG0mEWk25PEbLHhs7v.md b/src/data/roadmaps/bi-analyst/content/skewness@X0DBG0mEWk25PEbLHhs7v.md index 824d7a1f8..dd3170aec 100644 --- a/src/data/roadmaps/bi-analyst/content/skewness@X0DBG0mEWk25PEbLHhs7v.md +++ b/src/data/roadmaps/bi-analyst/content/skewness@X0DBG0mEWk25PEbLHhs7v.md @@ -1 +1,8 @@ -# Skewness \ No newline at end of file +# Skewness + +Skewness is a measure of the asymmetry of a distribution. A distribution is asymmetrical when its left and right side are not mirror images. A distribution can have right (or positive), left (or negative), or zero skewness, where the tails are roughly equal. A right-skewed distribution is longer on the right side of its peak, and a left-skewed distribution is longer on the left side of its peak. This measure helps understand data structure, the presence of outliers, and its suitability for statistical analyses. + +Visit the following resources to learn more: + +- [@article@Skewness](https://en.wikipedia.org/wiki/Skewness) +- [@article@Skewness | Definition, Examples & Formula](https://www.scribbr.com/statistics/skewness/) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/soft-skills@mi88uLdJBXaxJ2yVOSqqo.md b/src/data/roadmaps/bi-analyst/content/soft-skills@mi88uLdJBXaxJ2yVOSqqo.md index 51bcf0fc5..70d233693 100644 --- a/src/data/roadmaps/bi-analyst/content/soft-skills@mi88uLdJBXaxJ2yVOSqqo.md +++ b/src/data/roadmaps/bi-analyst/content/soft-skills@mi88uLdJBXaxJ2yVOSqqo.md @@ -1 +1,8 @@ -# Soft Skills \ No newline at end of file +# Soft Skills + +Soft skills are personal attributes that enable someone to interact effectively and harmoniously with other people. These skills, like communication, teamwork, and problem-solving, are crucial for building strong relationships, navigating complex situations, and achieving shared goals. They complement technical abilities and contribute significantly to overall professional success by fostering collaboration, understanding, and a positive work environment. + +Visit the following resources to learn more: + +- [@article@The Skills You Need to Work in Business Intelligence Analytics](https://tripleten.com/blog/posts/the-skills-you-need-to-work-in-business-intelligence-analytics) +- [@article@10 Essential Soft Skills for Data Analysts](https://bigblue.academy/en/soft-skills-for-data-analysts) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/sql-fundamentals@s8LZgRwrlm1V4meGM7gj0.md b/src/data/roadmaps/bi-analyst/content/sql-fundamentals@s8LZgRwrlm1V4meGM7gj0.md index bae1c8cb5..0f577db94 100644 --- a/src/data/roadmaps/bi-analyst/content/sql-fundamentals@s8LZgRwrlm1V4meGM7gj0.md +++ b/src/data/roadmaps/bi-analyst/content/sql-fundamentals@s8LZgRwrlm1V4meGM7gj0.md @@ -1 +1,8 @@ -# SQL Fundamentals \ No newline at end of file +# SQL Fundamentals + +SQL stands for Structured Query Language. It is a standardized programming language designed to manage and interact with relational database management systems (RDBMS). SQL allows you to create, read, edit, and delete data stored in database tables by writing specific queries. + +Visit the following resources to learn more: + +- [@article@Tutorial - Essential SQL For The Beginners](https://www.sqltutorial.org/) +- [@official@SQL Roadmap](https://roadmap.sh/sql) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/sql@_iV_5O5Rq07P9qRGrraTM.md b/src/data/roadmaps/bi-analyst/content/sql@_iV_5O5Rq07P9qRGrraTM.md index b4f9b4011..755b9190d 100644 --- a/src/data/roadmaps/bi-analyst/content/sql@_iV_5O5Rq07P9qRGrraTM.md +++ b/src/data/roadmaps/bi-analyst/content/sql@_iV_5O5Rq07P9qRGrraTM.md @@ -1 +1,7 @@ -# SQL \ No newline at end of file +# SQL for Exploratory Data Analysis + +SQL is a powerful tool for exploring data because it lets you quickly look at large datasets. You can use SQL to filter data based on specific conditions, calculate summary statistics like averages and counts, and group data to see patterns. Its simple syntax makes it easy to write queries to understand the characteristics of your data, identify potential issues, and prepare it for further analysis. + +Visit the following resources to learn more: + +- [@video@51:14 YouTube · Data with Baraa SQL Exploratory Data Analysis (EDA) Project](https://www.youtube.com/watch?v=6cJ5Ji8zSDg) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/sqlite@lrksz861rE5m2XzOQPwgh.md b/src/data/roadmaps/bi-analyst/content/sqlite@lrksz861rE5m2XzOQPwgh.md index 64d1d7121..d048bd380 100644 --- a/src/data/roadmaps/bi-analyst/content/sqlite@lrksz861rE5m2XzOQPwgh.md +++ b/src/data/roadmaps/bi-analyst/content/sqlite@lrksz861rE5m2XzOQPwgh.md @@ -1 +1,11 @@ -# SQLite \ No newline at end of file +# SQLite + +SQLite is a lightweight, serverless, self-contained SQL database engine that is designed for simplicity and efficiency. It is widely used in embedded systems and applications where a full-featured database server is not required, such as mobile apps, desktop applications, and small to medium-sized websites. SQLite stores data in a single file, which makes it easy to deploy and manage. It supports standard SQL queries and provides ACID (Atomicity, Consistency, Isolation, Durability) compliance to ensure data integrity. SQLite’s small footprint, minimal configuration, and ease of use make it a popular choice for applications needing a compact, high-performance database solution. + +Visit the following resources to learn more: + +- [@official@SQLite](https://www.sqlite.org/index.html) +- [@article@SQLite Tutorial](https://www.sqlitetutorial.net/) +- [@article@SQLite Introduction](https://www.youtube.com/watch?v=8Xyn8R9eKB8) +- [@article@Explore top posts about SQLite](https://app.daily.dev/tags/sqlite?ref=roadmapsh) +- [@video@SQLite Introduction - Beginners Guide to SQL and Databases](https://www.youtube.com/watch?v=8Xyn8R9eKB8) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/stakeholder-identification@e3SdmNpVcvy3k_-JIO6OK.md b/src/data/roadmaps/bi-analyst/content/stakeholder-identification@e3SdmNpVcvy3k_-JIO6OK.md index ef9cb22e4..490a7ff94 100644 --- a/src/data/roadmaps/bi-analyst/content/stakeholder-identification@e3SdmNpVcvy3k_-JIO6OK.md +++ b/src/data/roadmaps/bi-analyst/content/stakeholder-identification@e3SdmNpVcvy3k_-JIO6OK.md @@ -1 +1,7 @@ -# Stakeholder Identification \ No newline at end of file +# Stakeholder Identification + +**Stakeholder identification** is the process of determining who the key individuals or groups are that have an interest in, or are affected by, a project or business initiative. This involves understanding their roles, influence, and potential impact on the project's success. Identifying stakeholders early and accurately is crucial for effective communication, managing expectations, and ensuring that the project aligns with the needs and goals of all relevant parties. + +Visit the following resources to learn more: + +- [@video@4 Most Common Stakeholders in Business Intelligence](https://www.youtube.com/watch?v=iPfwEjRhm7w) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/stakeholder-management@r-m88g8xrUnuEpV2lHJfN.md b/src/data/roadmaps/bi-analyst/content/stakeholder-management@r-m88g8xrUnuEpV2lHJfN.md index afa2f043a..ecdeca247 100644 --- a/src/data/roadmaps/bi-analyst/content/stakeholder-management@r-m88g8xrUnuEpV2lHJfN.md +++ b/src/data/roadmaps/bi-analyst/content/stakeholder-management@r-m88g8xrUnuEpV2lHJfN.md @@ -1 +1,3 @@ -# Stakeholder Management \ No newline at end of file +# Stakeholder Management + +Stakeholder management involves identifying individuals or groups who have an interest in a project or business outcome and then developing strategies to effectively communicate with and manage their expectations. This includes understanding their needs, addressing their concerns, and ensuring their involvement throughout the project lifecycle to achieve successful results and maintain positive relationships. \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/standardisation@TCYG6vmFqq1zAPNQWoOH8.md b/src/data/roadmaps/bi-analyst/content/standardisation@TCYG6vmFqq1zAPNQWoOH8.md index 9f0b6f229..6ec77790f 100644 --- a/src/data/roadmaps/bi-analyst/content/standardisation@TCYG6vmFqq1zAPNQWoOH8.md +++ b/src/data/roadmaps/bi-analyst/content/standardisation@TCYG6vmFqq1zAPNQWoOH8.md @@ -1 +1,7 @@ -# Standardisation \ No newline at end of file +# Data Standardisation + +Data standardisation is the process of transforming data into a consistent and uniform format. This involves converting data values to a common unit, format, or scale, ensuring that different data sources can be easily compared and analysed. This process helps to eliminate inconsistencies and ambiguities, leading to more accurate and reliable insights. + +Visit the following resources to learn more: + +- [@article@Data Standardization: How It's Done & Why It's Important](https://www.simplilearn.com/what-is-data-standardization-article) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/star-vs-snowflake-schema@iYe42G31fhkAO0MBaHutF.md b/src/data/roadmaps/bi-analyst/content/star-vs-snowflake-schema@iYe42G31fhkAO0MBaHutF.md index 023e5296f..823333807 100644 --- a/src/data/roadmaps/bi-analyst/content/star-vs-snowflake-schema@iYe42G31fhkAO0MBaHutF.md +++ b/src/data/roadmaps/bi-analyst/content/star-vs-snowflake-schema@iYe42G31fhkAO0MBaHutF.md @@ -1 +1,13 @@ -# Star vs Snowflake Schema \ No newline at end of file +# Star vs. Snowflake Schema + +# Star vs Snowflake Schema + +A star schema is a way to organize data in a database, namely in data warehouses, to make it easier and faster to analyze. At the center, there's a main table called the **fact table**, which holds measurable data like sales or revenue. Around it are **dimension tables**, which add details like product names, customer info, or dates. This layout forms a star-like shape. + +A snowflake schema is another way of organizing data. In this schema, dimension tables are split into smaller sub-dimensions to keep data more organized and detailed, just like snowflakes in a large lake. + +The star schema is simple and fast -ideal when you need to extract data for analysis quickly. On the other hand, the snowflake schema is more detailed. It prioritizes storage efficiency and managing complex data relationships. + +Visit the following resources to learn more: + +- [@article@Star Schema vs Snowflake Schema: Differences & Use Cases](https://www.datacamp.com/blog/star-schema-vs-snowflake-schema) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/statistical-tests@01k_mfsp0eW6TX9yp8PDE.md b/src/data/roadmaps/bi-analyst/content/statistical-tests@01k_mfsp0eW6TX9yp8PDE.md index 2c96be9fc..788cf4c51 100644 --- a/src/data/roadmaps/bi-analyst/content/statistical-tests@01k_mfsp0eW6TX9yp8PDE.md +++ b/src/data/roadmaps/bi-analyst/content/statistical-tests@01k_mfsp0eW6TX9yp8PDE.md @@ -1 +1,8 @@ -# Statistical tests \ No newline at end of file +# Statistical Tests + +Statistical tests are methods used to determine if there's enough evidence to reject a null hypothesis. They help us decide whether observed differences or relationships in data are likely due to a real effect or simply due to random chance. These tests involve calculating a test statistic and comparing it to a critical value or calculating a p-value to assess the strength of the evidence against the null hypothesis. The choice of a specific statistical test, like a t-test or chi-square test, depends on the research design, data type (e.g., normal distribution), and the variables being analyzed. + +Visit the following resources to learn more: + +- [@article@Choosing the Right Statistical Test | Types & Examples](https://www.scribbr.com/statistics/statistical-tests/) +- [@article@List of statistical tests](https://en.wikipedia.org/wiki/List_of_statistical_tests) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/std@vqtzg9bydAqHMwZhPHo1a.md b/src/data/roadmaps/bi-analyst/content/std@vqtzg9bydAqHMwZhPHo1a.md index fd39f6952..2142d312e 100644 --- a/src/data/roadmaps/bi-analyst/content/std@vqtzg9bydAqHMwZhPHo1a.md +++ b/src/data/roadmaps/bi-analyst/content/std@vqtzg9bydAqHMwZhPHo1a.md @@ -1 +1,8 @@ -# STD \ No newline at end of file +# Standard Deviation (STD) + +The sample standard deviation is a statistical measure used to quantify the variation within a dataset. Specifically, it tells us how much individual data points in a sample differ from the sample mean. It's calculated as the square root of the variance. A low standard deviation indicates that the data points are generally close to the mean, while a high standard deviation implies that the data points are spread out over a wider range + +Visit the following resources to learn more: + +- [@article@Standard Deviation Formula and Uses vs. Variance](https://www.investopedia.com/terms/s/standarddeviation.asp) +- [@article@Standard Deviation](https://www.youtube.com/watch?v=esskJJF8pCc) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/storytelling-framework@t_J0MZTMWMnrImGHjXYov.md b/src/data/roadmaps/bi-analyst/content/storytelling-framework@t_J0MZTMWMnrImGHjXYov.md index b666eb0b9..c401ed4e4 100644 --- a/src/data/roadmaps/bi-analyst/content/storytelling-framework@t_J0MZTMWMnrImGHjXYov.md +++ b/src/data/roadmaps/bi-analyst/content/storytelling-framework@t_J0MZTMWMnrImGHjXYov.md @@ -1 +1,8 @@ -# Storytelling Framework \ No newline at end of file +# Storytelling Framework + +A storytelling framework provides a structured approach to crafting narratives from data insights. It typically involves defining the audience, identifying the key message, structuring the narrative with a clear beginning, middle, and end, and using visuals to support the story. This framework helps to present data in a compelling and easily understandable way, ensuring the audience grasps the significance of the findings. + +Visit the following resources to learn more: + +- [@article@3 Storytelling Frameworks I Am Using To Transform My Content Writing](https://writingcooperative.com/3-storytelling-frameworks-i-am-using-to-transform-my-content-writing-8433c83ce87e) +- [@video@Visual storytelling 101: elevating presentations with data visualization](https://www.youtube.com/watch?v=NXx0xQn7OXI) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/strategic-bi@3BxbkrBp8veZj38zdwN8s.md b/src/data/roadmaps/bi-analyst/content/strategic-bi@3BxbkrBp8veZj38zdwN8s.md index 980c99381..5c8a8cbdb 100644 --- a/src/data/roadmaps/bi-analyst/content/strategic-bi@3BxbkrBp8veZj38zdwN8s.md +++ b/src/data/roadmaps/bi-analyst/content/strategic-bi@3BxbkrBp8veZj38zdwN8s.md @@ -1 +1,3 @@ -# Strategic BI \ No newline at end of file +# Strategic planning + +Strategic planning defines an organization's long-term vision and high-level goals, while operational planning breaks these goals into short-term, detailed tasks and daily actions to achieve them. Strategic actions, designed for the long term, generally cover a period of 5 to 10 years. \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/structured@jnIn3_2fI2k97oALPZkt7.md b/src/data/roadmaps/bi-analyst/content/structured@jnIn3_2fI2k97oALPZkt7.md index fde643119..a770e18e4 100644 --- a/src/data/roadmaps/bi-analyst/content/structured@jnIn3_2fI2k97oALPZkt7.md +++ b/src/data/roadmaps/bi-analyst/content/structured@jnIn3_2fI2k97oALPZkt7.md @@ -1 +1,3 @@ -# Structured \ No newline at end of file +# Structured Data + +Structured data refers to information organized in a predefined format, typically stored in relational databases. This data has a defined length and type, making it easily searchable and analyzable. Common examples include data found in spreadsheets or SQL databases, where information is organized into rows and columns. \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/supervised-learning@eZN_ty8VDX9mi5KtCWTFL.md b/src/data/roadmaps/bi-analyst/content/supervised-learning@eZN_ty8VDX9mi5KtCWTFL.md index cc80ec827..4736b089b 100644 --- a/src/data/roadmaps/bi-analyst/content/supervised-learning@eZN_ty8VDX9mi5KtCWTFL.md +++ b/src/data/roadmaps/bi-analyst/content/supervised-learning@eZN_ty8VDX9mi5KtCWTFL.md @@ -1 +1,9 @@ -# Supervised Learning \ No newline at end of file +# Supervised Learning + +Supervised machine learning forms an integral part of the toolset for a Data Analyst. With a direct focus on building predictive models from labeled datasets, it involves training an algorithm based on these known inputs and outputs, helping Data Analysts establish correlations and make reliable predictions. Fortifying a Data Analyst's role, supervised machine learning enables the accurate interpretation of complex data, enhancing decision-making processes. + +Visit the following resources to learn more: + +- [@article@What is Supervised Learning?](https://cloud.google.com/discover/what-is-supervised-learning) +- [@article@Supervised Learning](ttps://www.datacamp.com/blog/supervised-machine-learning) +- [@video@Supervised Machine Learning Explained For Beginners](https://www.youtube.com/watch?v=Mu3POlNoLdc&pp=0gcJCf8Ao7VqN5tD) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/supply-chain-analytics@7jrzQogTOc6lHXfpYLCsx.md b/src/data/roadmaps/bi-analyst/content/supply-chain-analytics@7jrzQogTOc6lHXfpYLCsx.md index fdbbde566..795b65bda 100644 --- a/src/data/roadmaps/bi-analyst/content/supply-chain-analytics@7jrzQogTOc6lHXfpYLCsx.md +++ b/src/data/roadmaps/bi-analyst/content/supply-chain-analytics@7jrzQogTOc6lHXfpYLCsx.md @@ -1 +1,7 @@ -# Supply Chain Analytics \ No newline at end of file +# Supply Chain Analytics + +Supply Chain Analytics involves using data to understand and improve all aspects of a company's supply chain, from sourcing raw materials to delivering finished products to customers. This includes analyzing data related to inventory levels, transportation costs, supplier performance, and demand forecasting to identify bottlenecks, optimize processes, and reduce costs. The goal is to create a more efficient, responsive, and resilient supply chain. + +Visit the following resources to learn more: + +- [@article@What Is Supply Chain Analytics?](https://www.ibm.com/think/topics/supply-chain-analytics) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/supply-chain-optimization@-hNguvT6SQCqAgVpoQByr.md b/src/data/roadmaps/bi-analyst/content/supply-chain-optimization@-hNguvT6SQCqAgVpoQByr.md index 00878b823..b2fdb4eed 100644 --- a/src/data/roadmaps/bi-analyst/content/supply-chain-optimization@-hNguvT6SQCqAgVpoQByr.md +++ b/src/data/roadmaps/bi-analyst/content/supply-chain-optimization@-hNguvT6SQCqAgVpoQByr.md @@ -1 +1,8 @@ -# Supply chain optimization \ No newline at end of file +# Supply Chain Optimization + +Supply chain optimization involves streamlining the processes of sourcing, production, and distribution to maximize efficiency and minimize costs. It focuses on improving the flow of goods, information, and finances across the entire supply chain, from raw materials to the end customer. This includes strategies for inventory management, transportation, warehousing, and demand forecasting to ensure the right products are available at the right place, at the right time, and at the right cost. + +Visit the following resources to learn more: + +- [@article@How supply chain analytics keeps processes and products moving](https://www.teradata.com/insights/data-analytics/supply-chain-analytics) +- [@article@Enhance Efficiency: Supply Chain Analytics in Manufacturing](https://www.scatterpie.io/blogs/supply-chain-analytics-in-manufacturing) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/tableau@WzPj94lYxQCjFx5YW4X9x.md b/src/data/roadmaps/bi-analyst/content/tableau@WzPj94lYxQCjFx5YW4X9x.md index 46f5ae982..1353b0107 100644 --- a/src/data/roadmaps/bi-analyst/content/tableau@WzPj94lYxQCjFx5YW4X9x.md +++ b/src/data/roadmaps/bi-analyst/content/tableau@WzPj94lYxQCjFx5YW4X9x.md @@ -1 +1,9 @@ -# Tableau \ No newline at end of file +# Tableau + +Tableau is a powerful data visualization tool utilized extensively by data analysts worldwide. Its primary role is to transform raw, unprocessed data into an understandable format without any technical skills or coding. Data analysts use Tableau to create data visualizations, reports, and dashboards that help businesses make more informed, data-driven decisions. They also use it to perform tasks like trend analysis, pattern identification, and forecasts, all within a user-friendly interface. Moreover, Tableau's data visualization capabilities make it easier for stakeholders to understand complex data and act on insights quickly. + +Visit the following resources to learn more: + +- [@official@Tableau](https://www.tableau.com/en-gb) +- [@video@What is Tableau?](https://www.youtube.com/watch?v=NLCzpPRCc7U) +- [@video@Learn Tableau in Under 2 hours](https://www.youtube.com/watch?v=j8FSP8XuFyk) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/tactical-bi@jJukG4XxfFcID_VlQKqe-.md b/src/data/roadmaps/bi-analyst/content/tactical-bi@jJukG4XxfFcID_VlQKqe-.md index 872a591e6..32348e60b 100644 --- a/src/data/roadmaps/bi-analyst/content/tactical-bi@jJukG4XxfFcID_VlQKqe-.md +++ b/src/data/roadmaps/bi-analyst/content/tactical-bi@jJukG4XxfFcID_VlQKqe-.md @@ -1 +1,5 @@ -# Tactical BI \ No newline at end of file +# Tactical BI + +Tactical planning is responsible for establishing goals and conditions for the actions to be carried out outlined in strategic planning. Moreover, assessing and monitoring risks to address them effectively is essential. + +While strategic planning covers the entire organization, tactical planning operates on a more limited scale. It is implemented at the departmental level, sometimes focusing on specific end-to-end processes, and usually covers a period of 1 to 3 years. \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/time-series-analysis@yseEaLsEzIcqJ0YIoGujl.md b/src/data/roadmaps/bi-analyst/content/time-series-analysis@yseEaLsEzIcqJ0YIoGujl.md index 121a88e49..62be3cdd3 100644 --- a/src/data/roadmaps/bi-analyst/content/time-series-analysis@yseEaLsEzIcqJ0YIoGujl.md +++ b/src/data/roadmaps/bi-analyst/content/time-series-analysis@yseEaLsEzIcqJ0YIoGujl.md @@ -1 +1,11 @@ -# Time Series Analysis \ No newline at end of file +# Time Series Analysis + +Time series analysis is a statistical method used to analyze data points collected over time to identify patterns, trends, and seasonal variations. It involves examining a sequence of data points indexed in time order, allowing for forecasting future values based on historical observations. This analysis helps in understanding the underlying processes that generate the data and predicting future behavior. + +Visit the following resources to learn more: + +- [@article@Time series](https://en.wikipedia.org/wiki/Time_series) +- [@article@Time Series Analysis: Definition, Types & Techniques](https://www.tableau.com/analytics/what-is-time-series-analysis) +- [@article@Introduction to Time Series Analysis](https://www.itl.nist.gov/div898/handbook/pmc/section4/pmc4.htm) +- [@video@What is Time Series Analysis?](https://www.youtube.com/watch?v=GE3JOFwTWVM) +- [@video@Complete Time Series Analysis and Forecasting with Python](https://www.youtube.com/watch?v=eKiXtGzEjos) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/timeliness@5USjYdAVJs0gSXxE1j8Xu.md b/src/data/roadmaps/bi-analyst/content/timeliness@5USjYdAVJs0gSXxE1j8Xu.md index b97a70bdd..2a60e59a8 100644 --- a/src/data/roadmaps/bi-analyst/content/timeliness@5USjYdAVJs0gSXxE1j8Xu.md +++ b/src/data/roadmaps/bi-analyst/content/timeliness@5USjYdAVJs0gSXxE1j8Xu.md @@ -1 +1,3 @@ -# Timeliness \ No newline at end of file +# Timeliness + +Timeliness, in the context of data quality, refers to how up-to-date data is when it's needed. It measures the gap between when data is expected and when it's actually available for use. Data that is too old or delayed can lead to inaccurate analysis and poor decision-making. \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/trends@On6kznZxLTCpBPskdZtgT.md b/src/data/roadmaps/bi-analyst/content/trends@On6kznZxLTCpBPskdZtgT.md index 9965f7760..c84c6f963 100644 --- a/src/data/roadmaps/bi-analyst/content/trends@On6kznZxLTCpBPskdZtgT.md +++ b/src/data/roadmaps/bi-analyst/content/trends@On6kznZxLTCpBPskdZtgT.md @@ -1 +1,7 @@ -# Trends \ No newline at end of file +# Trends in Time Series Analysis + +Trends in time series analysis refer to the long-term movement or direction of data points in a dataset over a period of time. Identifying trends helps to understand the underlying patterns and predict future values. These trends can be upward (increasing), downward (decreasing), or stationary (relatively constant) and are often analyzed to make informed decisions and forecasts. + +Visit the following resources to learn more: + +- [@article@Complete Time Series Analysis and Forecasting with Python](https://www.youtube.com/watch?v=eKiXtGzEjos) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/types-of-bi-operations@LjeipkY01Hlkp22kmlAMh.md b/src/data/roadmaps/bi-analyst/content/types-of-bi-operations@LjeipkY01Hlkp22kmlAMh.md index b7e313fea..c5787270e 100644 --- a/src/data/roadmaps/bi-analyst/content/types-of-bi-operations@LjeipkY01Hlkp22kmlAMh.md +++ b/src/data/roadmaps/bi-analyst/content/types-of-bi-operations@LjeipkY01Hlkp22kmlAMh.md @@ -1 +1,3 @@ -# Types of BI Operations \ No newline at end of file +# Types of BI Operations + +Business operations are traditionally grouped in 3 hierarchical levels of management: strategic, tactical, and operational operations, each with a different scope, time frame, and purpose. \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/types-of-data-analysis@3DVF8zo-_WM_9GTuzQFO8.md b/src/data/roadmaps/bi-analyst/content/types-of-data-analysis@3DVF8zo-_WM_9GTuzQFO8.md index b1525da5c..a21b87677 100644 --- a/src/data/roadmaps/bi-analyst/content/types-of-data-analysis@3DVF8zo-_WM_9GTuzQFO8.md +++ b/src/data/roadmaps/bi-analyst/content/types-of-data-analysis@3DVF8zo-_WM_9GTuzQFO8.md @@ -1 +1,16 @@ -# Types of Data Analysis \ No newline at end of file +# Types of Data Analysis + +Data Analytics has proven to be a critical part of decision-making in modern business ventures. It is responsible for discovering, interpreting, and transforming data into valuable information. Different types of data analytics look at past, present, or predictive views of business operations. + +BI Analysts, as ambassadors of this domain, employ these types, to answer various questions: + +Descriptive Analytics (what happened in the past?) +Diagnostic Analytics (why did it happened in the past?) +Predictive Analytics (what will happen in the future?) +Prescriptive Analytics (how can we make it happen?) + +Visit the following resources to learn more: + +- [@article@The 4 Types of Data Analysis: Ultimate Guide](https://careerfoundry.com/en/blog/data-analytics/different-types-of-data-analysis/) +- [@video@Descriptive vs Diagnostic vs Predictive vs Prescriptive Analytics: What's the Difference?](https://www.youtube.com/watch?v=QoEpC7jUb9k) +- [@video@Types of Data Analytics](https://www.youtube.com/watch?v=lsZnSgxMwBA) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/types-of-data@H1s1PQj8CHQ_VBQIy1VtJ.md b/src/data/roadmaps/bi-analyst/content/types-of-data@H1s1PQj8CHQ_VBQIy1VtJ.md index 6fc5a45cb..6617c6e01 100644 --- a/src/data/roadmaps/bi-analyst/content/types-of-data@H1s1PQj8CHQ_VBQIy1VtJ.md +++ b/src/data/roadmaps/bi-analyst/content/types-of-data@H1s1PQj8CHQ_VBQIy1VtJ.md @@ -1 +1,7 @@ -# Types of data \ No newline at end of file +# Types of data + +Data types are categorized into structured, unstructured, and semi-structured data, differing in their organization and format + +Visit the following resources to learn more: + +- [@article@Data Basics: Structured, Unstructured, and Semi-structured Data](https://www.alation.com/blog/structured-unstructured-semi-structured-data/) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/types-of-errors@SosOXxErMn0t2KCoHoxvS.md b/src/data/roadmaps/bi-analyst/content/types-of-errors@SosOXxErMn0t2KCoHoxvS.md index dde8fbc45..2137be71d 100644 --- a/src/data/roadmaps/bi-analyst/content/types-of-errors@SosOXxErMn0t2KCoHoxvS.md +++ b/src/data/roadmaps/bi-analyst/content/types-of-errors@SosOXxErMn0t2KCoHoxvS.md @@ -1 +1,7 @@ -# Types of Errors \ No newline at end of file +# Types of Errors + +In hypothesis testing, a Type I error (false positive) occurs when you incorrectly reject a true null hypothesis, while a Type II error (false negative) happens when you fail to reject a false null hypothesis. These are the two types of mistakes that can be made when deciding whether to accept or reject the null hypothesis, with their probabilities denoted by alpha (α) and beta (β), respectively. + +Visit the following resources to learn more: + +- [@article@Type I & Type II Errors | Differences, Examples, Visualizations](https://www.scribbr.com/statistics/type-i-and-type-ii-errors/) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/unstructured@DJKXgelIxuahxJiqvwP6I.md b/src/data/roadmaps/bi-analyst/content/unstructured@DJKXgelIxuahxJiqvwP6I.md index 67af6f336..6fd0daad7 100644 --- a/src/data/roadmaps/bi-analyst/content/unstructured@DJKXgelIxuahxJiqvwP6I.md +++ b/src/data/roadmaps/bi-analyst/content/unstructured@DJKXgelIxuahxJiqvwP6I.md @@ -1 +1,3 @@ -# Unstructured \ No newline at end of file +# Unstructured Data + +Unstructured data refers to information that doesn't have a predefined format or organization. This type of data is typically text-heavy but can also include multimedia like images, audio, and video files. Because it lacks a structured format, it's more challenging to process and analyze directly compared to structured data. \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/unsupervised-learning@6l_tHC1R5zgABHMc_G6RD.md b/src/data/roadmaps/bi-analyst/content/unsupervised-learning@6l_tHC1R5zgABHMc_G6RD.md index a0216c8b4..936c10072 100644 --- a/src/data/roadmaps/bi-analyst/content/unsupervised-learning@6l_tHC1R5zgABHMc_G6RD.md +++ b/src/data/roadmaps/bi-analyst/content/unsupervised-learning@6l_tHC1R5zgABHMc_G6RD.md @@ -1 +1,9 @@ -# Unsupervised Learning \ No newline at end of file +# Unsupervised Learning + +Unsupervised learning, as a fundamental aspect of Machine Learning, holds great implications in the realm of data analytics. It is an approach where a model learns to identify patterns and relationships within a dataset that isn't labelled or classified. It is especially useful for a Data Analyst as it can assist in recognizing unforeseen trends, providing new insights or preparing data for other machine learning tasks. This ability to infer without direct supervision allows a vast potential for latent structure discovery and new knowledge derivation from raw data. + +Visit the following resources to learn more: + +- [@article@What is Unsupervised Learning?](https://cloud.google.com/discover/what-is-unsupervised-learning) +- [@article@Introduction to Unsupervised Learning](https://www.datacamp.com/blog/introduction-to-unsupervised-learning) +- [@video@Unsupervised Machine Learning Explained For Beginners](https://www.youtube.com/watch?v=yteYU_QpUxs&pp=ygUbI3doYXRpc3Vuc3VwZXJ2aXNlZGxlYXJuaW5n) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/variables-and-data-types@HM1w6JJquaV6Vq4mjxM7p.md b/src/data/roadmaps/bi-analyst/content/variables-and-data-types@HM1w6JJquaV6Vq4mjxM7p.md index 8782f0618..88c3d4c3f 100644 --- a/src/data/roadmaps/bi-analyst/content/variables-and-data-types@HM1w6JJquaV6Vq4mjxM7p.md +++ b/src/data/roadmaps/bi-analyst/content/variables-and-data-types@HM1w6JJquaV6Vq4mjxM7p.md @@ -1 +1,8 @@ -# Variables and Data Types \ No newline at end of file +# Variables and Data Types + +Variables are characteristics or attributes that can be measured or counted, and they can take on different values. Data types classify these variables based on the kind of values they can hold, such as numbers (integers, decimals), text (strings), or logical values (true/false). Understanding variables and their data types is fundamental for organizing, analyzing, and interpreting data effectively. + +Visit the following resources to learn more: + +- [@article@Variable Data Types Explained](https://www.freecodecamp.org/news/variable-data-types-explained/) +- [@article@Intro to Statistics](https://www.udacity.com/course/intro-to-statistics--st101) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/variance@ZmSwDn0sP7HvLKYVzRwPJ.md b/src/data/roadmaps/bi-analyst/content/variance@ZmSwDn0sP7HvLKYVzRwPJ.md index 655fea164..e04010781 100644 --- a/src/data/roadmaps/bi-analyst/content/variance@ZmSwDn0sP7HvLKYVzRwPJ.md +++ b/src/data/roadmaps/bi-analyst/content/variance@ZmSwDn0sP7HvLKYVzRwPJ.md @@ -1 +1,12 @@ -# Variance \ No newline at end of file +# Variance + +The variance measures the spread between numbers in a dataset. Simply put, it measures how far each number in the set is from the mean (average). It helps us understand how spread out or consistent the values are in a dataset. + +Variance is calculated by averaging the squared differences from the mean. First, find the mean of your data set. Then, subtract the mean from each data point, square those differences, sum them up, and finally, divide by either (n-1) for a sample or n for a population, where n is the number of data points. + +Variance can't be interpreted in the original units of measurement due to its squared nature, which is why it is often used in conjunction with its square root, the standard deviation. + +Visit the following resources to learn more: + +- [@article@What is Variance?](https://www.investopedia.com/terms/v/variance.asp) +- [@article@How to Calculate Variance](https://www.scribbr.co.uk/stats/variance-meaning) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/visualization-best-practices@eKBORkRU6HCH-D4GWHyKR.md b/src/data/roadmaps/bi-analyst/content/visualization-best-practices@eKBORkRU6HCH-D4GWHyKR.md index 26d5e6e14..f28b60c37 100644 --- a/src/data/roadmaps/bi-analyst/content/visualization-best-practices@eKBORkRU6HCH-D4GWHyKR.md +++ b/src/data/roadmaps/bi-analyst/content/visualization-best-practices@eKBORkRU6HCH-D4GWHyKR.md @@ -1 +1,8 @@ -# Visualization Best Practices \ No newline at end of file +# Visualization Best Practices + +Visualization best practices are a set of guidelines and principles that help you create effective and informative data visualizations. These practices focus on clarity, accuracy, and aesthetics to ensure that your visualizations communicate insights clearly and avoid misleading interpretations. They cover aspects like choosing the right chart type, using color effectively, and designing layouts that are easy to understand. + +Visit the following resources to learn more: + +- [@article@Data Visualization Tips and Best Practices](https://www.tableau.com/visualization/data-visualization-best-practices) +- [@article@Visual Best Practices](https://help.tableau.com/current/blueprint/en-us/bp_visual_best_practices.htm) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/visualization-fundamentals@sltVKaKKjmzu17jDv9OFF.md b/src/data/roadmaps/bi-analyst/content/visualization-fundamentals@sltVKaKKjmzu17jDv9OFF.md index b07f7fb08..77e1671d5 100644 --- a/src/data/roadmaps/bi-analyst/content/visualization-fundamentals@sltVKaKKjmzu17jDv9OFF.md +++ b/src/data/roadmaps/bi-analyst/content/visualization-fundamentals@sltVKaKKjmzu17jDv9OFF.md @@ -1 +1,10 @@ -# Visualization Fundamentals \ No newline at end of file +# Visualization Fundamentals + +Data visualization is the graphical representation of information and data. By using visual elements like charts, graphs, and maps, data visualization tools provide an accessible way to see and understand trends, outliers, and patterns in data. It transforms raw data into meaningful insights, making it easier to identify relationships and draw conclusions. + +Visit the following resources to learn more: + +- [@article@What Is Data Visualization? Definition, Examples, And Learning Resources](https://www.tableau.com/visualization/what-is-data-visualization) +- [@article@Fundamentals of Data Visualization](https://clauswilke.com/dataviz/introduction.html) +- [@book@The Ultimate Data Visualization Handbook for Designers](https://uxmag.medium.com/the-ultimate-data-visualization-handbook-for-designers-efa7d6e0b6fe) +- [@course@Business Intelligence Fundamentals](https://www.simplilearn.com/free-business-intelligence-course-online-skillup) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/web@xQLsuJ3uohVzOxGfFLyFw.md b/src/data/roadmaps/bi-analyst/content/web@xQLsuJ3uohVzOxGfFLyFw.md index 20e189d47..378bd66f4 100644 --- a/src/data/roadmaps/bi-analyst/content/web@xQLsuJ3uohVzOxGfFLyFw.md +++ b/src/data/roadmaps/bi-analyst/content/web@xQLsuJ3uohVzOxGfFLyFw.md @@ -1 +1,3 @@ -# Web \ No newline at end of file +# Web Data Sources + +Web data sources refer to information collected from the internet. This includes data scraped from websites, data from APIs (Application Programming Interfaces) that websites expose, and data collected through web analytics tools. This information can range from website traffic and user behavior to product pricing and social media trends. \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/what-is-bi@jVXwlHRGgVpcoWCYzSB5W.md b/src/data/roadmaps/bi-analyst/content/what-is-bi@jVXwlHRGgVpcoWCYzSB5W.md index 863a88cd5..cd752b157 100644 --- a/src/data/roadmaps/bi-analyst/content/what-is-bi@jVXwlHRGgVpcoWCYzSB5W.md +++ b/src/data/roadmaps/bi-analyst/content/what-is-bi@jVXwlHRGgVpcoWCYzSB5W.md @@ -1,3 +1,9 @@ # Business Intelligence (BI) -Business Intelligence (BI) involves using data to understand past and present business performance and to predict future trends. It encompasses the processes and technologies used to collect, analyze, and visualize data, ultimately helping organizations make better, data-driven decisions. This includes reporting, online analytical processing (OLAP), data mining, process mining, complex event processing, business performance management, benchmarking, and predictive analytics. \ No newline at end of file +Business Intelligence (BI) involves using data to understand past and present business performance and to predict future trends. It encompasses the processes and technologies used to collect, analyze, and visualize data, ultimately helping organizations make better, data-driven decisions. This includes reporting, online analytical processing (OLAP), data mining, process mining, complex event processing, business performance management, benchmarking, and predictive analytics. + +Visit the following resources to learn more: + +- [@article@What Is Business Intelligence - Microsoft](https://www.microsoft.com/en-us/power-platform/products/power-bi/topics/business-intelligence/what-is-business-intelligence) +- [@article@What Is Business Intelligence (BI)? - IBM](https://www.ibm.com/think/topics/business-intelligence) +- [@course@Business Intelligence Fundamentals](https://www.simplilearn.com/free-business-intelligence-course-online-skillup) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/what-is-data@g5j_mbjx2yZUIK5lfN3eT.md b/src/data/roadmaps/bi-analyst/content/what-is-data@g5j_mbjx2yZUIK5lfN3eT.md index 604374235..4f9fbdc24 100644 --- a/src/data/roadmaps/bi-analyst/content/what-is-data@g5j_mbjx2yZUIK5lfN3eT.md +++ b/src/data/roadmaps/bi-analyst/content/what-is-data@g5j_mbjx2yZUIK5lfN3eT.md @@ -1 +1,3 @@ -# What is Data? \ No newline at end of file +# What is Data? + +Data are facts or pieces of information. They are often measurements or observations, or opinions. Usually, data is collected to be analyzed to find insights, draw a conclusion, or make a decision. \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/why-bi-matters@NX-YaB_FVjoHYsR6z9QIL.md b/src/data/roadmaps/bi-analyst/content/why-bi-matters@NX-YaB_FVjoHYsR6z9QIL.md index 15b3a70c3..70677c266 100644 --- a/src/data/roadmaps/bi-analyst/content/why-bi-matters@NX-YaB_FVjoHYsR6z9QIL.md +++ b/src/data/roadmaps/bi-analyst/content/why-bi-matters@NX-YaB_FVjoHYsR6z9QIL.md @@ -1,3 +1,7 @@ # Why BI Matters -In today's data-driven world, organizations need to make informed decisions quickly and efficiently. Business Intelligence (BI) analysis and the role of a Business Analyst are crucial for transforming raw data into actionable insights. By identifying trends, patterns, and anomalies, BI helps organizations understand their performance, optimize processes, and gain a competitive edge. A skilled Business Analyst bridges the gap between data and business strategy, ensuring that insights are translated into tangible improvements and strategic advantages. \ No newline at end of file +In today's data-driven world, organizations need to make informed decisions quickly and efficiently. Business Intelligence (BI) analysis and the role of a Business Analyst are crucial for transforming raw data into actionable insights. By identifying trends, patterns, and anomalies, BI helps organizations understand their performance, optimize processes, and gain a competitive edge. A skilled Business Analyst bridges the gap between data and business strategy, ensuring that insights are translated into tangible improvements and strategic advantages. + +Visit the following resources to learn more: + +- [@course@Business Intelligence Fundamentals](https://www.simplilearn.com/free-business-intelligence-course-online-skillup) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/window-functions@1toMuRZResgse1AtwEck6.md b/src/data/roadmaps/bi-analyst/content/window-functions@1toMuRZResgse1AtwEck6.md index 42eff4a36..d644d878c 100644 --- a/src/data/roadmaps/bi-analyst/content/window-functions@1toMuRZResgse1AtwEck6.md +++ b/src/data/roadmaps/bi-analyst/content/window-functions@1toMuRZResgse1AtwEck6.md @@ -1 +1,9 @@ -# Window Functions \ No newline at end of file +# Window Functions + +Window functions in SQL perform calculations across a set of table rows that are related to the current row. Unlike aggregate functions that group rows into a single output row, window functions retain the individual rows while adding calculated values based on the window frame defined for each row. This allows you to compute things like running totals, moving averages, or rank values within a partition of your data without collapsing the original dataset. + +Visit the following resources to learn more: + +- [@article@SQL Window Functions](https://mode.com/sql-tutorial/sql-window-functions) +- [@article@SQL Window Functions Cheat Sheet](https://www.datacamp.com/cheat-sheet/sql-window-functions-cheat-sheet) +- [@official@SQL Roadmap](https://roadmap.sh/sql) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/writing-executive-summaries@Slg3fXGPTa-Z4sdZY86XK.md b/src/data/roadmaps/bi-analyst/content/writing-executive-summaries@Slg3fXGPTa-Z4sdZY86XK.md index 67693f98e..99dcfeee0 100644 --- a/src/data/roadmaps/bi-analyst/content/writing-executive-summaries@Slg3fXGPTa-Z4sdZY86XK.md +++ b/src/data/roadmaps/bi-analyst/content/writing-executive-summaries@Slg3fXGPTa-Z4sdZY86XK.md @@ -1 +1,7 @@ -# Writing Executive Summaries \ No newline at end of file +# Writing Executive Summaries + +Executive summaries are concise overviews of longer reports or analyses, designed to quickly inform decision-makers. The best executive summaries clearly state the problem or opportunity, the key findings, the recommended actions, and the expected benefits. They should be brief, typically no more than one page, and written in plain language, avoiding technical jargon. Prioritize clarity and focus on the most important information, ensuring the summary is easily understood and actionable. + +Visit the following resources to learn more: + +- [@article@How to write an executive summary, with examples](https://asana.com/resources/executive-summary-examples) \ No newline at end of file diff --git a/src/data/roadmaps/bi-analyst/content/xml@ytgK7van84j5DsfD0JyZ3.md b/src/data/roadmaps/bi-analyst/content/xml@ytgK7van84j5DsfD0JyZ3.md index 74967b1fc..75cfed96a 100644 --- a/src/data/roadmaps/bi-analyst/content/xml@ytgK7van84j5DsfD0JyZ3.md +++ b/src/data/roadmaps/bi-analyst/content/xml@ytgK7van84j5DsfD0JyZ3.md @@ -1 +1,7 @@ -# XML \ No newline at end of file +# XML + +XML (Extensible Markup Language) is a markup language designed for encoding documents in a format that is both human-readable and machine-readable. It uses tags to define elements and attributes to describe the properties of those elements, allowing for structured data representation and exchange between different systems and applications. XML's hierarchical structure makes it suitable for representing complex data relationships. + +Visit the following resources to learn more: + +- [@article@XML](https://en.wikipedia.org/wiki/XML) \ No newline at end of file