Skip to main content
cancel
Showing results for 
Search instead for 
Did you mean: 

Enhance your career with this limited time 50% discount on Fabric and Power BI exams. Ends September 15. Request your voucher.

Reply
GregMarbais
Kudo Collector
Kudo Collector

Dataflow Gen2 Enable Staging

Has anyone started using the Enable Staging feature in Dataflow Gen 2 and noticed a substantial increase in CU usage? I used it for some of my more complex tables but the CU % jumped from roughly 50% of capacity beforehand to well over 1000% after (I double checked). I disabled staging and now am back to normal. So I wanted to see when staging tables in DFG2 is beneficial over not using it? And if anyone has a sense of how it impacts capacity usage.

For reference, we're on an F64 sku. And I've built out a pretty substantial set of dataflows and lakehouses. I was only using the Enable Staging on some of the more complicated tables that merge multiple tables created from other dataflows.

1 ACCEPTED SOLUTION
Anonymous
Not applicable

Hi @GregMarbais ,

 

Staging is beneficial in the following situations:

  1. High Scale Compute is required, allowing for faster execution and efficient data processing.
  2. Temporal Consistency across downstream dataflows is needed to ensure data integrity.
  3. Reduced Load on Source Systems by minimizing the number of queries submitted to the data source.
  4. Data Reconciliation Processes where a copy of the source data is useful for validating transformations downstream.

 

Given your situation with an F64 SKU and substantial dataflows and lakehouses setup, it's important to balance the benefits of staging with the impact on CU usage. The substantial increase in CU usage you've observed suggests that the complexity and volume of your dataflows, when combined with Enable Staging, exceed the expected CU consumption for your SKU.

 

Action Plan:

  1. Review Dataflow Design: Consider optimizing your dataflows to reduce complexity where possible. This might involve simplifying transformations or splitting large dataflows into smaller, more manageable pieces.
  2. Monitor CU Consumption: Keep a close eye on CU usage patterns to identify specific dataflows or operations that contribute most to the increase. This can help in pinpointing areas for optimization.
  3. Consider SKU Adjustment: If the benefits of Enable Staging are critical for your scenarios, evaluating whether a different SKU might better accommodate your CU usage needs could be worthwhile.

For more insights on managing and optimizing dataflows in Power BI, I recommend reviewing the guidance on Power BI usage scenarios: Advanced data preparation - Power BI | Microsoft Learn

 

Best Regards,

Neeko Tang

If this post  helps, then please consider Accept it as the solution  to help the other members find it more quickly. 

View solution in original post

1 REPLY 1
Anonymous
Not applicable

Hi @GregMarbais ,

 

Staging is beneficial in the following situations:

  1. High Scale Compute is required, allowing for faster execution and efficient data processing.
  2. Temporal Consistency across downstream dataflows is needed to ensure data integrity.
  3. Reduced Load on Source Systems by minimizing the number of queries submitted to the data source.
  4. Data Reconciliation Processes where a copy of the source data is useful for validating transformations downstream.

 

Given your situation with an F64 SKU and substantial dataflows and lakehouses setup, it's important to balance the benefits of staging with the impact on CU usage. The substantial increase in CU usage you've observed suggests that the complexity and volume of your dataflows, when combined with Enable Staging, exceed the expected CU consumption for your SKU.

 

Action Plan:

  1. Review Dataflow Design: Consider optimizing your dataflows to reduce complexity where possible. This might involve simplifying transformations or splitting large dataflows into smaller, more manageable pieces.
  2. Monitor CU Consumption: Keep a close eye on CU usage patterns to identify specific dataflows or operations that contribute most to the increase. This can help in pinpointing areas for optimization.
  3. Consider SKU Adjustment: If the benefits of Enable Staging are critical for your scenarios, evaluating whether a different SKU might better accommodate your CU usage needs could be worthwhile.

For more insights on managing and optimizing dataflows in Power BI, I recommend reviewing the guidance on Power BI usage scenarios: Advanced data preparation - Power BI | Microsoft Learn

 

Best Regards,

Neeko Tang

If this post  helps, then please consider Accept it as the solution  to help the other members find it more quickly. 

Helpful resources

Announcements
August Power BI Update Carousel

Power BI Monthly Update - August 2025

Check out the August 2025 Power BI update to learn about new features.

August 2025 community update carousel

Fabric Community Update - August 2025

Find out what's new and trending in the Fabric community.