Boosting Data Loading Speed in Power BI with Parquet Format

Often, the analyses you are asked to perform in Power BI need to be based on fairly large data sources. In the previous chapter, you learned how to work with data that is larger than the RAM available on your machine, and you saw that query execution times are in the order of minutes.

Now consider a report that needs to perform several calculations on the same corpus database. Obviously, the performance of the overall execution time of the report is strongly related to the expected number of operations to be performed on the database. Therefore, being able to reduce the execution time of individual queries will allow you to have a report whose dataset is updated as quickly as possible with each refresh.

Queries implemented in a Power BI report most often need to retrieve aggregated measures that provide users with the information they need to take specific business actions. If the data is available in relational databases...