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Hi @Anonymous
User-defined aggregations in Power BI serve the primary purpose of improving query performance, especially when working with large DirectQuery semantic models.
They achieve this by caching data at an aggregated level in memory, allowing Power BI to retrieve summarized data from the cache rather than executing potentially slow queries against the underlying data source for every visual interaction.
It is oftenly used with dual storage mode, if you are using a large model, you can create an aggregation table for your import dataset and use a direct query to get the details of the last transactions
Radcad wrote some usefuls articles about this topic:
Let me know if you need more help to understand this concept
Hi @Anonymous
User-defined aggregations in Power BI serve the primary purpose of improving query performance, especially when working with large DirectQuery semantic models.
They achieve this by caching data at an aggregated level in memory, allowing Power BI to retrieve summarized data from the cache rather than executing potentially slow queries against the underlying data source for every visual interaction.
It is oftenly used with dual storage mode, if you are using a large model, you can create an aggregation table for your import dataset and use a direct query to get the details of the last transactions
Radcad wrote some usefuls articles about this topic:
Let me know if you need more help to understand this concept
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