Get certified for free when you join Fabric Data Days 2026 and dive into Fabric, Power BI, SQL, AI, and other essential data skills.
Join nowJuly 28 - August 9 | Final Round of the Power BI Dataviz World Championships. This is your chance. Learn more
I am working with a dataset where Row-Level Security (RLS) is implemented, and we have multiple thin reports. We now have a requirement for one of these thin reports to display global numbers, effectively overriding the RLS implementation.
My current solution involves creating duplicate tables (both dimension and fact tables) specifically for this report to bypass RLS. However, this approach leads to having multiple fact tables with millions of rows, which significantly increases the dataset size and computational overhead.
Is there a more optimal way to achieve this without duplicating large fact tables? Any suggestions or best practices would be greatly appreciated.
My dax to filter the dataset looks like this.
Is there a more optimal way to achieve this without duplicating large fact tables?
Not really. Consider using separate reports/audiences. But the data duplication is required.
Join us in Barcelona for FabCon and SQLCon, the Fabric, Power BI, SQL, and AI community event. Save €200 with code FABCMTY200.
If you love stickers, then you will definitely want to check out our community sticker challenge, Barcelona edition!
Check out the July 2026 Power BI update to learn about new features.
| User | Count |
|---|---|
| 30 | |
| 28 | |
| 24 | |
| 23 | |
| 16 |
| User | Count |
|---|---|
| 46 | |
| 32 | |
| 17 | |
| 17 | |
| 16 |