Data Transformation

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

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

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 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. 

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

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

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.

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

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

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

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

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

Use PDF conversion tools to disassemble and assemble tables within PDF documents

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

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

Explore structured columns containing Lists, Records or Tables

Using in-built standard Excel tools, we will explore how to reduce uncertainty in decision-making with sensitivity and scenario analysis

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

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

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

Challenge your data skills in creating an analysis report on substance

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

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

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

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

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!