Summary

In this chapter, we learned how to speed up Power BI datasets in Import mode. We began with some theory on Kimball dimensional modeling, where we learned about star schemas, which are built from facts and dimensions. Data modeling is about grouping and relating attributes, and star schemas are one way to model data. They provide non-technical users with an intuitive way to analyze data by combining qualitative attributes into dimension tables. These dimensions are related to fact tables, which contain qualitative attributes. Power BI's Analysis Services engine works extremely well with star schemas, which are preferred. Hence, we briefly looked at the four-step dimensional modeling process and provided a practical example, including one with many-to-many relationships.

Then, we focused on reducing the size of datasets. This is important because less data means less processing, which results in better performance and more free resources for other parallel operations...