For DirectQuery semantic models, this feature studies the query log with machine learning and then creates and maintains in-memory summaries by itself; any aggregations you've defined manually continue to work next to them.
Read more: Microsoft Learn
In the Ultra Transcenders books
Each book explains Automatic aggregations in context, with comparison tables and the common traps.
Terms in this definition
- DirectQuery
Power BI connection mode in which reports fetch data from the source in real time; Direct Lake outperforms it.
- ML
Building models that infer patterns from data so they can predict outcomes, for instance through regression or classification, using tools like Azure Machine Learning or Synapse Spark pools. Predictive ML is distinct from generative AI.
- Aggregations
Summary queries over a large DirectQuery table can be answered from memory instead of the source thanks to this semantic model feature: it keeps a concealed summary table cached and sends qualifying queries there, while anything needing fine detail still goes back to the source.
- NEXT
Restricted to visual calculations, this DAX function reads the value one step further along an axis of the visual matrix; writing OFFSET with 1 gives the same result.
Related terms
- Take over
Only an owner can set up scheduled refresh, data source credentials and automatic aggregations for a semantic model. This action, in the model's settings in the service, transfers ownership to whoever selects it.