Forum Discussion
Optimizing Performance for Power BI Reports with Large Datasets and Complex Measures
- Anonymous1 year ago
Hi MicrosoftMaster,
I think this should be a normal loading time based on your report data amount, calculations and design.
Is it possible to reduce the stored data amount and calculation fields? Or you can try to switch to live connection mode and put the Dax expressions to the database side?Regards,
Xiaoxin Sheng
- 1 year ago
Hi,
Thank you for your suggestion. Unfortunately, I’m unable to reduce the stored data amount or move the DAX expressions to the database side. As per our team's procedures, all measures must remain in the dataset, and we use a live connection for our reporting setup. This approach ensures consistency across multiple reports and datasets.
If you have any alternative recommendations that work within these constraints, I’d be happy to explore them!
- 1 year ago
Anything above 5 seconds leads to bad user experience. Continue learning about how to use DAX Studio to optimize your measures (SQLBI.com has tons of training videos on that topic). Refactor your queries so they use fewer resources.
Anything above 5 seconds leads to bad user experience. Continue learning about how to use DAX Studio to optimize your measures (SQLBI.com has tons of training videos on that topic). Refactor your queries so they use fewer resources.
Thank you for your feedback! I’ll definitely explore SQLBI.com.
I wanted to ask for clarification regarding backend solutions. For instance, in some applications, performance can be improved by adding resources like CPU, memory, or storage. In the case of Power BI, are performance issues typically resolved solely by query optimization, or is there scope to address them by adjusting capacity or increasing resources?
Currently, I’m using Fabric capacity on Power BI.
- lbendlin1 year agoSuper User
Depends on the connection type. For import mode data sources your only option is to optimize the DAX code. For Direct Query data sources you can also look at the SQL code generated by the queries and apply optimizations at the source (indexes, statistics etc).