Data Transformation

This path is focused on developing expert level skills in data cleaning, data transformation and data modeling. You will learn to maximize the capabilities of the Power Query UI, and also write M code.

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

This Learning Path delves into data analysis techniques, focusing on Power BI functions. It guides learners to enhance their data insight extraction skills.

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

This path is designed to build the broad range of expert-level knowledge necessary to confidently pass the PL-300 Data Analyst certification exam (replacement for DA-100).

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

Discover how to utilize ChatGPT within Power BI for enhanced data analysis, reporting, and interactive dashboards. Learn how to integrate ChatGPT into Power BI to create dynamic and conversational visualizations.

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

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

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

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

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.

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

Find out how Sidekick can help to review, optimize & cleanup your dataset and reports

Enterprise DNA Analytics Summit are action packed live events showcasing a variety of beginner to advanced Power BI & Power Platform tips and techniques. 

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

Know the techniques in creating indexes and how to loop efficiently using DAX

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

How to build the ultimate Stream Deck profile - perform an array of common Power BI tasks at the push of a button

Create advanced analytical models by learning how to harness the power of DAX calculations for use within Power BI

See the Deneb custom visual for Power BI in-action with start-to-finish development of a bullet chart, a ring chart, and linked charts in Deneb/Vega-Lite

Create an analysis report on environmental data and potentially impact how this data is visualized and recorded

Challenge your data skills by creating a report on transport and shipping data 

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

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

Take a deep dive into the world of utilisation and timesheet data

Work on one of the most significant measures for manufacturing productivity - OEE

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

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

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.

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

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!