chore: sync content to repo (#9591)

Co-authored-by: kamranahmedse <4921183+kamranahmedse@users.noreply.github.com>
2026-10-24 23:06:33 +08:00 · 2026-02-06 14:30:16 +01:00
parent 9a7e557276
commit e8017f3e85
34 changed files with 66 additions and 63 deletions
@@ -5,4 +5,5 @@ Accessibility in data visualization focuses on designing charts and graphs that
 Visit the following resources to learn more:

 - [@article@10 Guidelines for DataViz Accessibility](https://www.highcharts.com/blog/tutorials/10-guidelines-for-dataviz-accessibility/)
+- [@article@5 Crucial Tweaks That Will Make Your Charts Accessible to People with Visual Impairments](https://towardsdatascience.com/5-crucial-tweaks-that-will-make-your-charts-accessible-to-people-with-visual-impairments/?utm_source=roadmap&utm_medium=Referral&utm_campaign=TDS+roadmap+integration)
 - [@video@Accessibility in Data Visualisation](https://www.youtube.com/watch?v=OOPeS_xWoKQ)
@@ -4,5 +4,5 @@ Advanced SQL queries go beyond basic data retrieval and manipulation. They invol

 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)
+- [@official@SQL Roadmap](https://roadmap.sh/sql)
+- [@article@25 Advanced SQL Query Examples](https://learnsql.com/blog/25-advanced-sql-query-examples/)
@@ -6,5 +6,5 @@ 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)
+- [@video@Apache Airflow Tutorial for Data Engineers](https://www.youtube.com/watch?v=y5rYZLBZ_Fw)
+- [@feed@Explore top posts about Apache Airflow](https://app.daily.dev/tags/apache-airflow?ref=roadmapsh)
@@ -4,6 +4,6 @@ Machine learning fundamentals encompass the key concepts and techniques that ena

 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/)
+- [@course@MLCourse.ai](https://mlcourse.ai/)
+- [@article@What Is Machine Learning (ML)?](https://www.ibm.com/think/topics/machine-learning)
@@ -4,6 +4,6 @@ Learning how to make basic SQL queries in esencial for BI analysts. Queries are

 Visit the following resources to learn more:

+- [@official@SQL Roadmap](https://roadmap.sh/sql)
 - [@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)
+- [@article@Basic SQL Commands](https://www.freecodecamp.org/news/basic-sql-commands/)
@@ -1,9 +1,9 @@
 # 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.
+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:

+- [@course@Intro to Inferential Statistics](https://www.udacity.com/course/intro-to-inferential-statistics--ud201)
 - [@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)
+- [@video@Nonlinear regression - the basics](https://www.youtube.com/watch?v=4hYGiG4qVf4)
@@ -1,6 +1,6 @@
 # BI Analyst vs. Other Roles

-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.
+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:

@@ -4,7 +4,7 @@ Communication and storytelling involve conveying insights and findings from data

 Visit the following resources to learn more:

+- [@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)
 - [@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)
+- [@video@Telling Stories with Data in 3 Steps (Quick Study)](https://www.youtube.com/watch?v=r5_34YnCmMY)
@@ -4,6 +4,6 @@ Correlation analysis is a statistical method used to determine the strength and

 Visit the following resources to learn more:

+- [@course@Intro to Inferential Statistics](https://www.udacity.com/course/intro-to-inferential-statistics--ud201)
 - [@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)
+- [@article@Correlation](https://en.wikipedia.org/wiki/Correlation)
@@ -4,6 +4,6 @@ Correlation describes the degree to which two variables tend to move together, i

 Visit the following resources to learn more:

+- [@course@Intro to Inferential Statistics](http://udacity.com/course/intro-to-inferential-statistics--ud201)
 - [@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)
+- [@article@Correlation does not imply causation](https://en.wikipedia.org/wiki/Correlation_does_not_imply_causation)
@@ -1,4 +1,4 @@
-# CSV 
+# 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.

@@ -1,4 +1,4 @@
-# Data lakes 
+# 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.

@@ -2,11 +2,11 @@

 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
+*   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.

@@ -4,6 +4,6 @@ dbt, also known as the data build tool, is designed to simplify the management o

 Visit the following resources to learn more:

+- [@course@dbt Official Course](https://learn.getdbt.com/catalog)
 - [@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)
+- [@official@dbt Docs](https://docs.getdbt.com/docs/build/documentation)
@@ -1,7 +1,9 @@
+# undefined
+
 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)
+- [@article@Intro to Statistics](https://www.udacity.com/course/intro-to-statistics--st101)
+- [@video@Statistics 101 - Measures of Dispersion](https://www.youtube.com/watch?v=goXdWMZxlqM)
@@ -4,7 +4,7 @@ Inferential statistics uses sample data to make inferences or predictions about

 Visit the following resources to learn more:

+- [@course@Intro to Inferential Statistics](https://www.udacity.com/course/intro-to-inferential-statistics--ud201)
 - [@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)
+- [@video@Inferential Statistics FULL Tutorial](https://www.youtube.com/watch?v=6E6pB5JFLgM)
@@ -4,6 +4,6 @@ Linear regression is a statistical method used to model the relationship between

 Visit the following resources to learn more:

+- [@course@Intro to Inferential Statistics](https://www.udacity.com/course/intro-to-inferential-statistics--ud201)
 - [@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)
+- [@article@Linear regression](https://en.wikipedia.org/wiki/Linear_regression)
@@ -1,4 +1,4 @@
-# Mean 
+# 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.

@@ -1,4 +1,4 @@
-# Median 
+# 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.

@@ -1,3 +1,5 @@
+# undefined
+
 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:
@@ -4,6 +4,6 @@ SQL performance tuning involves optimizing SQL queries and database structures t

 Visit the following resources to learn more:

+- [@official@SQL Roadmap](https://roadmap.sh/sql)
 - [@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)
+- [@article@Performance Tuning SQL Queries](https://mode.com/sql-tutorial/sql-performance-tuning)
@@ -5,8 +5,8 @@ PostgreSQL is an advanced, open-source relational database management system (RD
 Visit the following resources to learn more:

 - [@roadmap@Visit Dedicated PostgreSQL DBA Roadmap](https://roadmap.sh/postgresql-dba)
+- [@course@PostgreSQL: Become an SQL developer](https://www.simplilearn.com/free-postgresql-course-skillup)
 - [@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)
+- [@feed@Explore top posts about PostgreSQL](https://app.daily.dev/tags/postgresql?ref=roadmapsh)
@@ -1,4 +1,4 @@
-# Predictive analysis 
+# 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.

@@ -5,7 +5,7 @@ Python is a versatile and widely-used programming language known for its readabi
 Visit the following resources to learn more:

 - [@roadmap@Visit Dedicated Python Roadmap](https://roadmap.sh/python)
+- [@book@Python for Data Analysis](https://datapot.vn/wp-content/uploads/2023/12/datapot.vn-Python-for-Data-Analysis.pdf?srsltid=AfmBOopeeuwebcpwD9crBjnMo3wchpUtvkz-g1T2Phi7FFyjkx7l5t9e)
 - [@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)
+- [@video@Ultimate Data Analyst Bootcamp [24 Hours!]](https://www.youtube.com/watch?v=wQQR60KtnFY)
@@ -4,7 +4,7 @@ R is a programming language and free software environment widely used for statis

 Visit the following resources to learn more:

- [@official@R](https://www.r-project.org/)
 - [@book@R for Data Science](https://r4ds.hadley.nz/)
+- [@official@R](https://www.r-project.org/)
 - [@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)
@@ -4,6 +4,6 @@ Regression analysis is a form of predictive modelling technique which investigat

 Visit the following resources to learn more:

+- [@course@Intro to Inferential Statistics](https://www.udacity.com/course/intro-to-inferential-statistics--ud201)
 - [@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)
+- [@article@A Refresher on Regression Analysis - Harvard](https://hbr.org/2015/11/a-refresher-on-regression-analysis)
@@ -4,7 +4,7 @@ Reinforcement learning is a type of machine learning where an agent learns to ma

 Visit the following resources to learn more:

+- [@course@Deep Reinforcement Learning Course by HuggingFace](https://huggingface.co/learn/deep-rl-course/unit0/introduction)
 - [@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)
@@ -4,5 +4,5 @@ SQL stands for Structured Query Language. It is a standardized programming langu

 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)
+- [@official@SQL Roadmap](https://roadmap.sh/sql)
+- [@article@Tutorial - Essential SQL For The Beginners](https://www.sqltutorial.org/)
@@ -1,10 +1,11 @@
 # Star vs. Snowflake Schema

-# 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. 
+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.

@@ -4,10 +4,7 @@ Data Analytics has proven to be a critical part of decision-making in modern bus

 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?)
+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:

@@ -1,8 +1,8 @@
 # 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. 
+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 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.

@@ -4,7 +4,7 @@ Data visualization is the graphical representation of information and data. By u

 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)
+- [@course@Business Intelligence Fundamentals](https://www.simplilearn.com/free-business-intelligence-course-online-skillup)
+- [@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)
@@ -4,6 +4,6 @@ Business Intelligence (BI) involves using data to understand past and present bu

 Visit the following resources to learn more:

+- [@course@Business Intelligence Fundamentals](https://www.simplilearn.com/free-business-intelligence-course-online-skillup)
 - [@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)
+- [@article@What Is Business Intelligence (BI)? - IBM](https://www.ibm.com/think/topics/business-intelligence)
@@ -4,6 +4,6 @@ Window functions in SQL perform calculations across a set of table rows that are

 Visit the following resources to learn more:

+- [@official@SQL Roadmap](https://roadmap.sh/sql)
 - [@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)
+- [@article@SQL Window Functions Cheat Sheet](https://www.datacamp.com/cheat-sheet/sql-window-functions-cheat-sheet)