A recent Towards Data Science article offers a technical deep dive into how DAX filtering operates within Power BI, specifically examining the execution mechanics using DAX Studio. Author X explores the critical distinction between how the Formula Engine (FE) and Storage Engine (SE) handle filters, revealing surprising insights about performance and efficiency.

The analysis focuses on practical queries, demonstrating how filter placement—whether in the query itself or within measures—significantly impacts the underlying SE queries and execution plans. Key findings show the SE's ability to optimize queries, often reducing multiple filters into a single efficient execution path, while highlighting the pitfalls of overusing the FILTER() function.