Summary
In this chapter, we learned about optimizing model performance. We learned how some of the easiest ways to increase data model performance include only keeping data that is necessary for reports and either removing the additional rows and columns using Power Query, aggregating the data to reduce it, or simply removing the data in the underlying data store (sometimes accomplished with a view in a database). We also learned how to use tools such as DAX Studio to investigate the inner workings of measures to best optimize those components of our data models for the best performance. We learned how we can optimize relationships and visuals and how we can use the query diagnostics tools in Power BI to better understand the operations that take place in Power Query.
In the next chapter, we will learn about creating dynamic and engaging reports using Power BI Desktop.
