Power BI Best Practices – Improve report performance, …

Improving report performance in Power BI is crucial for delivering a smooth and responsive user experience. Here are some best practices to enhance report performance:

1. Data Model Optimization:

   • Use Import Mode: Import data into Power BI for optimal performance. Import mode stores a copy of the data in the Power BI file, reducing the need for real-time queries.
   • Remove Unused Columns: Eliminate unnecessary columns in your data model to reduce the size of the dataset.
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2. Data Transformation in Power Query:

   • Filter Data Early: Apply filters and transformations as early as possible in the Power Query Editor to reduce the amount of data loaded into Power BI.
   • Avoid Unnecessary Steps: Minimize unnecessary data transformation steps in Power Query to reduce processing time.

3. Relationships and Cardinality:

   • Optimize Relationships: Ensure relationships between tables are correctly configured. Avoid unnecessary relationships and use bi-directional filtering cautiously.
   • Avoid Many-to-Many Relationships: Limit the use of many-to-many relationships, as they can negatively impact performance.

4. DAX Optimization:

   • Use Aggregations: Create summary tables or aggregations to pre-calculate values and improve DAX query performance.
   • Avoid Iterative Functions: Minimize the use of iterative functions like ROW and FILTER in favor of set-based operations when possible.

5. Report Design:

   • Limit Visual Elements: Reduce the number of visuals on a report page to enhance responsiveness.
   • Use Slicers Wisely: Limit the number of slicers and avoid unnecessary slicer interactions.
   • Paginate Large Reports: Break down large reports into multiple pages or sections to avoid overwhelming the system.

6. Data Refresh:

   • Optimize Data Refresh: Schedule data refresh during non-business hours to minimize impact on users.
   • Incremental Refresh: Use incremental refresh for large datasets to only refresh new or modified data.

7. Power BI Desktop:

   • Disable Auto Date/Time: Turn off the auto date/time feature if it’s not required for your analysis.
   • Limit Data in Preview Mode: In Power BI Desktop, limit the amount of data loaded during report development to improve responsiveness.
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8. Use Summary Tables:

   • Create Summary Tables: When dealing with large datasets, consider creating summary tables to store pre-aggregated data.

9. Indexing in the Source Database:

   • Optimize Source Queries: Ensure that queries sent to the source database are optimized. Proper indexing in the source database can significantly improve query performance.

10. Monitor and Tune:

    • Use Performance Analyzer: Utilize the Performance Analyzer tool in Power BI Desktop to identify bottlenecks in report performance.
    • Power BI Service Metrics: Monitor performance metrics in the Power BI service to identify areas for improvement.

11. Implement Row-Level Security (RLS) Efficiently:

    • Optimize RLS Rules: If using Row-Level Security, ensure that the rules are efficient and don’t negatively impact performance.

12. Regularly Update Power BI Desktop and Service:

    • Stay Current: Keep Power BI Desktop and the Power BI service up to date to benefit from the latest performance improvements and features.
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