Microsoft Fabric Analytics Engineer Associate Study Guide

Chapter 5. Designing and Building Semantic Models

When working with Power BI, it’s easy to start with a simple data setup and let things grow over time, adding more tables to the model, more visuals to the report, more fields, and more measures. But at some point, maintaining performance and clarity can become a challenge. This chapter focuses on several ways to keep your model manageable, even as it grows.

We’ll start with the basics: choosing the right storage mode in Power BI. After that, we have a look at how to build relationships between tables and how to create a star schema. Relationships between tables are essential for creating a semantic model that performs well and behaves predictably when our users slice and filter the report.

Then, we’ll look at how to reduce the number of repetitive DAX measures by using calculation groups, and we’ll show you how we can use field parameters to give our report users control over what fields or measures are shown in the Power BI report.

Finally, we’ll look at two more advanced topics that are especially relevant in large enterprise models: the large semantic model storage format and building composite models.

Choosing a Storage Mode

When we begin developing a semantic model in Power BI, we need to select the storage mode that best suits our needs. Making the right choice is important because each mode has its own advantages and limitations that directly affect performance, flexibility, and how up-to-date our data is. Power BI has ...