Question

What strategies would you use to flush a Power BI model without affecting usability?

My Power BI model has grown significantly in size, and I need to reduce its memory footprint without compromising its functionality or usability. I’ve heard about techniques like removing unused columns and tables, but I’m not sure how to implement these changes efficiently. Could you provide strategies to optimize and flush a Power BI model effectively?

Answer 1

Remove the unused column and table for the optimization and model downsize while retaining usability. Explain the same using the view as table and performance analyzer to identify the unused fields. Summary aggregation should be used instead of detailed raw data wherever possible, especially for large tables. The data table needs to be optimized as well and has, at most, the necessary date range and columns.

Switch to a more efficient type. For example, where applicable, Text would be replaced by integers or booleans instead. Filter out the unnecessary rows in ETL, such as pre-aggregation of data in Power Query. Other things will be schematized using star schema modeling. It makes relationships easy and improves performance. Check for model size from time to time and the performance metrics to maintain the optimization.

Comments

Optimize Power BI by removing unused fields, using summary aggregation, switching to efficient data types, filtering unnecessary rows in ETL, applying star schema modeling, and monitoring performance metrics regularly.

Answer 2

To create a clear, readable matrix report in Power BI, enable Stepped Layout under Row Headers, adjust the spacing for better clarity, and use conditional formatting to highlight parent rows, ensuring easy interpretation of hierarchical data.