Power BI: Advanced Data Analysis Expressions (DAX)

Classical courses

Version: Microsoft 365
Duration: 1 day (09:00-17:00)
Price training (excl. VAT): €1425
Number of people: 1-12p


This course is specifically designed for experienced Power BI users who want to deepen their knowledge and skills in DAX (Data Analysis Expressions). DAX features are an essential part of Power BI that enables powerful data analysis and calculations. This course focuses on developing advanced DAX skills, enabling participants to perform complex calculations and extract deep insights from their data. Through hands-on exercises and examples, participants will learn how to effectively apply DAX within their Power BI projects.


After completing this Power BI course, you will be able to:

  • Work with (bidirectional) relationships in the model
  • Add measures, calculated columns and calculated tables to the model
  • Protect your data so that the end user only sees the data he is allowed to see

Target Group

This course is ideal for data analysts, business analysts, and Power BI developers who already have experience with Power BI and want to expand their analytical skills. It is perfect for professionals who want to get more out of their data and perform advanced analytics within Power BI.


Participants should have taken the introductory training course “Power BI: Core Features 1” or have a solid foundation of Power BI.


Part 1 Calculations (DAX)

  • Context (Difference between row context and filter context)
  • Functions (depending on time)
    • Filter functions (ex: All, AllSelected, Filter, Selectedvalue, Removefilters)
    • Time intelligence functions (ex: DateAdd, DatesBetween, DatesINPeriod, DatesYTD, SamePeriodLastYear)
    • Logic functions (ex: If, Switch, Coalesce)
    • Aggregation functions (ex: Countrows, SumX, Countblank, Distinctcount)
    • Relation functions (ex: Userelationship, Crossfilter, Relatedtable)
  • Calculate and CalculateTable
    • Add context
    • Change context
    • Remove context
    • Context transition (row context becomes filter context)
  • Using variables in measures
  • What if parameters

Part 2 Security

  • Row-level security (limit the data in a report to what may be visible to the end user)

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