Data Transformation

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 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 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 data visualization and analysis techniques, with a special emphasis on 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 Learning Path delves into Power BI development, focusing on creating effective reports and visualizations. It covers parameter management, using PowerPoint and more!

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. 

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.

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.

Acquire an extensive knowledge and understanding of the Power Query and M language to help you easily transform your data from multiple sources into Power BI

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

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

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

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

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

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

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

One of the break-out session in our Reporting & Data Visualization Summit, showcasing a variety of beginner to advanced Power BI tips and techniques.

Get to telling your story faster within power BI with various automation tools and techniques

Discover the key points around OEE and producing a technically sound report

Learn the best practices for transforming data in the query editor

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

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

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

Challenge your data skills in creating an analysis report on substance

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

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

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

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

Create a report summary of the overall services provided by a Call Centre for its management

Provide a business solution by creating an intelligence tool to use by large opticians

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.