DAX Tips, Tricks and Techniques

You cannot take shortcuts learning DAX. You must learn some theory first.

Some of the most common mistakes DAX developers make

More common mistakes DAX developers make

More common mistakes DAX developers make

More common mistakes DAX developers make

More common mistakes DAX developers make

A number of best practices for naming your DAX and data model objects

A best practice when creating temporary table columns and then referencing them later in DAX code

There are a number of things you need to be aware of when filtering data using the FILTER function. You will learn about them during this lecture.

The TREATAS function is not well known or often used but it can sure come in handy

Bidirectional filters sound like a great idea in theory, but there are some problems. You'll learn about them in this lecture.

If we shouldn't be using bidirectional filters, what should we be doing? You'll find out in this discussion.

The ALL family of functions can be tricky to use. You'll learn some best practices and techniques in this lecture.

We discuss a number of different ways to handle errors and potential errors in your DAX code.

When you need to start troubleshooting performance issues in your Power BI reports and DAX measures, you have a number of options you might not be aware of. You'll learn about various options in this talk.

More discussion about performance monitoring and the VertiPaq Analyzer

Introduction to this section

You will learn several tips for organizing your data models

You will learn the benefits of a star schema and why it's worth the effort to model your data this way

Learn how aggregation tables can greatly speed up the processing of your measures in large data models

Have you ever had a scenario where you had multiple dates in your fact table and you needed to create measures using those various dates? If you were not aware you could have active and inactive relationships between tables, you probably struggled with figuring out how to make this work efficiently. We'll show you how in this lecture.