Data Transformation

This Learning Path offers a comprehensive journey through advanced data analysis and modeling techniques all illustrated through practical scenarios.

This Learning Path navigates learners through real-world scenarios to cultivate problem-solving skills using the M language in Power Query.

This path is similar to the Data Analyst learning path above, but is geared to building a strong and broad foundation of data analysis skills, as compared to being more specifically focused on passing the PL 300 exam.

This Learning Path offers a comprehensive journey through data visualization and analysis techniques, with a special emphasis on Power BI.

This path is the most in-depth and rigorous on the list, designed to provide you expert-level skills in all of the key pillars of Power BI. 

This learning path offers a deep dive into data management and analysis, emphasizing the hands-on use of Python and Scala languages for manipulating CSV and JSON files, and the application of SQL for data querying. 

This path is designed to help you build expert level skills in the implementation, monitoring and governance of Power BI, including making optimal use of the Service through dataflows, datasets, thin reports, etc.

This path is designed to provide you the necessary skills to build full enterprise apps by integrating Power BI , Power Automate and Power Apps. 

Expand your Power BI report by integrating it with Power Platform applications to incorporate capabilities above and beyond just reporting on insights.

Get familiar with structured values in the M language and discover how to interact with them.

An in depth overview of the entire Power BI suite, with a focus on using Power BI to extract compelling insights from your own data.

Unlock the power of data analysis and visualization with PandasAI, and transform raw data into actionable insights that drive decision-making and growth.

Expand Power BI's capabilities in accessing a wide range of data using APIs

Learn how to clean, optimize and model data tables to develop effective, insightful and actionable Power BI reports

Deepen your understanding of the Power Query/M concepts through practical application

The first of the two-part preparation course for the Microsoft's DP-500 Exam Certification

Learn the best practices for transforming data in the query editor

This session will cover which Python and R packages and examples can facilitate functionalities found in Power BI

Learn the steps that an Enterprise BI team can take to implement application lifecycle management (ALM) in their Power BI environment

Learning how to use SELECT, FROM, WHERE, GROUP BY, HAVING, ORDER BY

Sneak Peak Into Upcoming Versions of HTML Custom Visuals with Pascal Kiefer

Create basic pipelines for data cleaning, visualization and modeling in R

Learn how to build external tools for Power BI. The highlights of what you need to do, what you need to be thinking about in terms of creating an external tool for Power BI

Why No-Code and Standardized Visualizations are the Future in Data Analytics and Visualizations

Challenge your data skills by producing a report that gives the user the ability to select a currency and see the associated sales and cost

Deep dive into the world of F1 and create an analysis of the drivers' stats

Take on the challenge of creating an analysis report on hotels revenue management data.

Implement your analytical skills in creating a report of the entire business operation from production to forecasting.

Analyze the data of a large insurance company who are due to undergo an internal audit with regard to its complaint’s procedure

Analyze Enterprise DNA's Youtube Channel Data to understand its audience and create a strategy to drive more channel engagement.

Challenge your data skills in creating an analysis report on substance

Produce insights for management level that can highlight any issues and prepare them for the audit

This SQL cheat sheet gives you the most common SQL objects and commands, including data types, DML and DDL statements, aggregate functions, string and date functions, and subqueries.

When programming in Python, having a reliable cheat sheet by your side can be a game-changer. Python may be known for its simplicity and readability, but there’s no denying that its extensive range of features and functionalities is too much to memorize!

This offers techniques to retrieve and manipulate data based on specific row indexes or key matches, enhancing the flexibility and precision of data analysis.