In Power BI projects, one of the first questions teams face is: should we rely on ETL pipelines or simply use Power Query for data preparation?
The right answer depends on scale, governance, refresh latency, and who will maintain the solution. Here’s a pragmatic way to choose.
What is ETL?
ETL (or ELT) refers to engineered data pipelines that extract from sources, transform with orchestrated logic, and land curated tables into a warehouse or data lake.
What is Power Query?
Power Query is the M engine embedded in Power BI (and other Microsoft tools) that lets analysts shape data step-by-step inside the BI layer.
ETL vs Power Query — Key Differences
When to Use ETL
When to Use Power Query
Hybrid Architecture (Best of Both)
Most high-performing teams blend the two: push heavy lifting to ETL, keep last-mile business logic in Power Query for agility.
Performance & Governance Tips
Quick Decision Matrix
Use these rules-of-thumb to decide where to implement a transformation:
Conclusion
There’s no rivalry—only fit for purpose. ETL provides scale, governance, and reuse; Power Query provides speed, proximity to business logic, and iteration.
Need help designing the right mix? Book a free, no-obligation strategy call and we’ll map the path from raw data to trusted insight.