Forum Discussion
Power Bi Report Server
- 8 months ago
Hi Bilge ,
When working with a 50GB SSAS Tabular model and a large user base, direct querying can cause performance challenges. Here are several strategies to help address this.
1. Pre aggregate frequent queries in SSAS so Power BI accesses smaller, faster datasets.
2. Divide the model into partitions, such as by date or region, to focus queries and improve speed.
3. Refresh only updated data instead of the entire model.
4. Use Import mode for smaller, commonly used data and DirectQuery for larger tables.
5. For SSAS Enterprise users, enable scale-out to balance query loads across multiple servers.
Refine DAX measures, minimize calculated columns, and ensure efficient relationships to reduce query time.
Applying these approaches can help maintain your SSAS model's integrity while keeping Power BI performance high for users.
Regards,
Yugandhar.
Hi Bilge,
Thinking about your question, in my oppinion:
A tabular model of 50 GB is extremely heavy for Power BI Report Server. This results in:
- High memory consumption: The VertiPaq engine must load the entire dataset into RAM, which can saturate the server.
- Very slow refresh times: Each refresh could take hours and affect other services.
- Limited scalability: Any further growth makes the model even harder to manage.
Use Microsoft Fabric
- Create a Lakehouse or Data Warehouse in Fabric to store the data in an optimised structure.
Alternative with SQL Server
- Expose the data through optimised views or stored procedures in SQL Server.
- Use DirectQuery in Power BI to avoid loading 50 GB into the model.
DirectQuery in Power BI: When to Use, Limitations, Alternatives - Power BI | Microsoft Learn
If this response was helpful in any way, Iād gladly accept a šmuch like the joy of seeing a DAX measure work first time without needing another FILTER.
Please mark it as the correct solution. It helps other community members find their way faster (and saves them from another endless loop š.