Hi,
Incremental refresh in Power BI is designed to improve refresh performance by only refreshing the data that has changed since the last refresh. It's generally recommended for large datasets where refreshing the entire dataset every time is time-consuming.
When working with incremental refresh, the underlying data source type (table or view) shouldn't significantly impact the performance. Both tables and views can be used with incremental refresh, and the choice between them depends on your data modeling and reporting needs.
you should check:
Table Structure: Make sure that the tables or views you are using have a column that can be used to identify new or modified rows. This column is important for the incremental refresh to work efficiently.
Indexes: In SQL, if you are using a view, make sure that the underlying tables have proper indexes to speed up the data extraction process. This is true for tables as well.
Query Complexity: Sometimes, the SQL query complexity for a view might be higher than for a simple table. If your view involves complex calculations or joins, it could impact refresh performance.
Partitioning: Check if your table or view can be partitioned effectively. Partitioning helps in loading only the required portions of data during a refresh.
Query Folding: Ensure that Power BI is able to "fold" your queries back to the source database. Query folding allows Power BI to push some operations back to the database, improving performance.
Read post about incremental refresh here:
https://analyticpulse.blogspot.com/2023/11/mastering-efficiency-with-incremental.html
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