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Hi ,
You can follow these points as a best practice:-
1)Limit the number of visuals in dashboards and reports
Using too many visuals on a single report slows report performance. Limit widget visuals to eight per report page and grids to one per page. Limit tiles to 10 per dashboard. In general, limit pages 30 points, assuming each type of visual is worth a different number of points:
2)Remove unnecessary interactions between visuals
By default, all visuals on a report page can interact with one another. By disabling unnecessary interactions, you reduce the number of queries fired at the back end, which improves report performance.
3) Use on-premises data gateway instead of Personal Gateway
Personal Gateway imports data into Power BI. On-premises data gateway (also known as Enterprise Gateway) imports nothing, which is more efficient when working with large databases.
4)Use separate gateways for Power BI service live connection and scheduled data refresh
If you use the same gateway for a scheduled refresh and a live connection, live connection performance will slow down during the scheduled refresh.
5)Test custom visual performance before use
Custom visuals can perform poorly when handling large datasets or complex aggregations. Uncertified custom visuals are generally not tested by the Power BI team. If a custom visual performs poorly, consider replacing it with a different visual.
6)Limit complex measures and aggregations in data models
Create calculated measures instead of calculated columns. Where possible, push calculated columns and measures to the source. The closer they are to the source, the faster they are likely to perform.
7)Use Star schema instead of Snowflake schema when possible
Snowflake schema has a complex query structure, making it difficult to implement changes. Star schema is easy to read, uses fewer joins, and tends to reduce data redundancy.
😎Use slicers sparingly
Slicers are a great way of allowing users to navigate data, but they come at a performance cost. Each slicer generates two queries: one fetches the data, the other fetches selection details. Adding too many slicers drastically slows performance. To remove unnecessary slicers, use the Filter pane to evaluate which slicers are used the least.
9) Ensure reports and data sources are in the same region
With the tenant and data source in the same region, you can limit the effects of network latency. Sharing a region ensures faster data transfer and faster query execution.
Please follow these link to read more:-
https://maqsoftware.com/insights/power-bi-best-practices
https://learn.microsoft.com/en-us/training/modules/optimize-model-power-bi/
https://www.phdata.io/blog/optimizing-power-bi-reports/
Thanks,
Pratyasha Samal
Has this post solved your problem? Please Accept as Solution so that others can find it quickly and to let the community know your problem has been solved.
If you found this post helpful, please give Kudos
Proud to be a Super User!
Hi ,
You can follow these points as a best practice:-
1)Limit the number of visuals in dashboards and reports
Using too many visuals on a single report slows report performance. Limit widget visuals to eight per report page and grids to one per page. Limit tiles to 10 per dashboard. In general, limit pages 30 points, assuming each type of visual is worth a different number of points:
2)Remove unnecessary interactions between visuals
By default, all visuals on a report page can interact with one another. By disabling unnecessary interactions, you reduce the number of queries fired at the back end, which improves report performance.
3) Use on-premises data gateway instead of Personal Gateway
Personal Gateway imports data into Power BI. On-premises data gateway (also known as Enterprise Gateway) imports nothing, which is more efficient when working with large databases.
4)Use separate gateways for Power BI service live connection and scheduled data refresh
If you use the same gateway for a scheduled refresh and a live connection, live connection performance will slow down during the scheduled refresh.
5)Test custom visual performance before use
Custom visuals can perform poorly when handling large datasets or complex aggregations. Uncertified custom visuals are generally not tested by the Power BI team. If a custom visual performs poorly, consider replacing it with a different visual.
6)Limit complex measures and aggregations in data models
Create calculated measures instead of calculated columns. Where possible, push calculated columns and measures to the source. The closer they are to the source, the faster they are likely to perform.
7)Use Star schema instead of Snowflake schema when possible
Snowflake schema has a complex query structure, making it difficult to implement changes. Star schema is easy to read, uses fewer joins, and tends to reduce data redundancy.
😎Use slicers sparingly
Slicers are a great way of allowing users to navigate data, but they come at a performance cost. Each slicer generates two queries: one fetches the data, the other fetches selection details. Adding too many slicers drastically slows performance. To remove unnecessary slicers, use the Filter pane to evaluate which slicers are used the least.
9) Ensure reports and data sources are in the same region
With the tenant and data source in the same region, you can limit the effects of network latency. Sharing a region ensures faster data transfer and faster query execution.
Please follow these link to read more:-
https://maqsoftware.com/insights/power-bi-best-practices
https://learn.microsoft.com/en-us/training/modules/optimize-model-power-bi/
https://www.phdata.io/blog/optimizing-power-bi-reports/
Thanks,
Pratyasha Samal
Has this post solved your problem? Please Accept as Solution so that others can find it quickly and to let the community know your problem has been solved.
If you found this post helpful, please give Kudos
Proud to be a Super User!
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