22-25 April 2026 
SQLBits 2024
Aggregations in Power BI
Introduce Power BI aggregations with practical examples, evaluate pros and cons, and learn how to use alternative approaches by using DAX to control the aggregation used.
Power BI provides manual and automatic aggregations to optimize queries on DirectQuery over SQL models. Pre-aggregated tables can highly improve the performance of the storage engine at the expense of storage and increased processing time.
In this session, we introduce the concept of aggregation; we show several examples of their usage, understanding the advantages and the limitations of aggregations, intending to build a solid understanding of how and when to use the feature in data models. Eventually, we will see how to control the use of manual aggregations in DAX, which can also be used with other storage engines such as VertiPaq and DirectLake.
In this session, we introduce the concept of aggregation; we show several examples of their usage, understanding the advantages and the limitations of aggregations, intending to build a solid understanding of how and when to use the feature in data models. Eventually, we will see how to control the use of manual aggregations in DAX, which can also be used with other storage engines such as VertiPaq and DirectLake.
Speakers
Marco Russo's previous sessions
Advanced DAX
Unleash the full power of evaluation context manipulation, learn about expanded tables, control the data lineage, avoid circular dependencies, and manage relationships at different granularities.
Aggregations in Power BI
Introduce Power BI aggregations with practical examples, evaluate pros and cons, and learn how to use alternative approaches by using DAX to control the aggregation used.
Using ALLEXCEPT or ALL/VALUES?
Learn when to use ALL / VALUES instead of ALLEXCEPT in DAX calculations.
Understanding window functions in DAX
Introduction to DAX window functions and apply semantics through several examples to understand their capabilities and performance.