Data Transformation

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

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 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).

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

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

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.

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

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

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

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

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

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

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

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

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

Know how to get DAX Query data from Power BI Desktop without having to write it yourself

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

Learn how to use Python to accomplish different outputs inside Power BI.

Critical thinking to improve problem solving and decision making

Know how to filter the data using what-if parameters

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

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

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

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

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

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

Challenge your data skills in creating an analysis report on substance

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

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.