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Power BI Data Analyst Associate (PL-300) Cert Prep: Create Model Calculations Using DAX

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The Power BI Data Analyst Associate certification is intended for data professionals who leverage Microsoft's Power BI data tool. This course is part of a series of courses designed to prepare for the Microsoft Power BI Data Analyst PL-300 exam. In this course, instructor Jermaine McDonald covers the exam topics relating to creating model calculations using the DAX modeling languages. Jermaine takes you step-by-step through three core areas you need to know for the exam: tables and relationships, functions, and measures. Learn about the different aspects of creating model calculations with DAX, including working with tables, unlocking the power of relationships, and common pitfalls in designing these relationshipsI. Get an overview of the functions used in DAX, with examples of how they work and relevant tips for the exam. Finally learn to create quick and full measures, decide between measures and calculated columns, and ways Power BI makes it easy to work with for data analysis.


01 - Introduction
  • 01 - Model the data in the PL-300 exam
  • 02 - Before you begin
  • 03 - Creating model calculations with DAX
  • 04 - Model design best practices
  • 05 - Power BI Desktop and the exercise files

  • 02 - 1. Tables and Relationships
  • 01 - Working with Tables Best practices
  • 02 - One-to-one relationships
  • 03 - One-to-many relationships
  • 04 - Many-to-many relationships
  • 05 - Common pitfalls in creating relationships

  • 03 - 2. Functions
  • 01 - Recap of functions
  • 02 - Row and filter contexts
  • 03 - Using the CALCULATE function
  • 04 - Creating dates with CALENDAR and CALENDARAUTO
  • 05 - Accessing related data with the RELATED function
  • 06 - Overriding default relationships with functions
  • 07 - Time-intelligence functions
  • 08 - Statistical functions

  • 04 - 3. Measures
  • 01 - Demo Creating a quick measure in Power BI
  • 02 - Demo Creating a full measure
  • 03 - Demo Semi-additive measures
  • 04 - Calculated columns vs. measures
  • 05 - Implicit vs. explicit measures
  • 06 - Work with aggregations
  • 07 - Demo Calculated tables

  • 05 - Conclusion
  • 01 - Next steps
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