There are two ways to solve any analytical problem: the right way and the wrong way. Most of the time, the right way involves building the correct data model first, and then authoring very simple DAX code. The wrong way would be creating a data model that just imports the available data, and then writing crazy DAX code to compute the required numbers.

This session introduces the basic principles of data modeling for analytics. We consider several scenarios where the data model makes a difference. This clarifies why a model is “right” or “wrong” and why spending enough time to design the right data model greatly pays back at the time of coding.

You can download slides and demos of this session using the link below.