Data Transformation

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 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 Learning Path dives into SharePoint and Power Apps, focusing on leveraging Power Automate for task automation and improved user interaction. 

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

This path is designed to help you harness the full power of Power BI in combination with R and Python. You will learn how to conduct advanced analyses and gain insight into complex business questions.

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

This Learning Path delves into Power BI development, focusing on creating effective reports and visualizations. It covers parameter management, using PowerPoint and more!

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

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.

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

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.

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

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

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

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

Know how to filter the data using what-if parameters

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

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

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

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

How to create your own custom quick measures - create once, and apply them in every future report you do

Using visual layering and transparency masks to improve data storytelling Advanced tricks for conditional formatting icons

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

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

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

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

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

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

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

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

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

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!