Key insights
- Table-level refresh: Refresh just one table in a semantic model instead of the whole model to save time and resources.
This is ideal when one table changed and the rest are stable.
- Refresh types: Choose between Data refresh (reload values), Schema refresh (apply structural changes), or both.
Pick the smallest scope that covers your change to speed up updates.
- Desktop vs Service: In Power BI Desktop you can right-click a table and select Refresh Data to update only that table.
The Power BI Service offers newer table-level options in Model Explorer, but older Service workflows rely on pipelines for granular control.
- Fabric Pipeline and partitions: Use a Fabric Pipeline with the Semantic Model Refresh activity to target specific tables or partitions.
Targeting a single partition is useful for large fact tables where only recent partitions change.
- Limitations: Direct Lake models do not support table-level refresh in the same way, and some refreshes may also touch tables that share the same data source.
Check your model type before relying on table-only updates.
- Scheduling and best practices: Schedule a pipeline refresh for recurring selective updates and combine this with incremental refresh to limit data movement.
This reduces runtime, cost, and the risk of unnecessary reprocessing.
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