Data Transformation

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

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

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

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

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.

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

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

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

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.

Critical thinking to improve problem solving and decision making

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

Learn necessary elements to resolve granularities mismatches in different ways

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

Create external tool to generate the Enterprise DNA extended date table (Holidays, Some Date Intelligence Measures, Set Sort By)

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

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

Learn how to use other data sources to filter and/or colorize individual objects of a 3D model in Power BI

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

Challenge your data skills in creating an analysis report on substance

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

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

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

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

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

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

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!