Forum Discussion
Data update in report combining Direct Query and OneLake Data Hub (Power BI Semantic Model)
I would have expected, that a change to S1 after publishing would immediately take effect on the R2 onlineThat is only true for data, and for varying interpretations of "immediately".
Meta data changes need to be propagated.
This behavior is indeed a limitation when using composite models that combine DirectQuery and a live connection (like OneLake Data Hub's semantic model). Here’s what’s happening and some options to consider:
1. Local Model Constraints: When you add DirectQuery sources to a report connected to a semantic model, Power BI creates a local model. Unfortunately, the local model does not automatically sync with updates made to the original semantic model. This limitation requires reopening, refreshing, and republishing the report to reflect any updates made to S1.
2. Alternative Approaches:
- Use DirectQuery Only: If feasible, consider sourcing all data via DirectQuery to avoid needing a local model. This allows your report to respond to live changes in connected data sources.
- Automate Desktop Refresh and Republish: Power Automate Desktop or other scheduling tools can help automate opening, refreshing, and publishing reports. While it doesn’t replace live syncing, it can minimize manual intervention.
- Dataflows as Intermediate Layer: If it’s feasible, use Dataflows for common data sources in S1 and S2. Then, have R2 pull from these Dataflows, which allows faster refreshes and somewhat centralizes updates.
Unfortunately, native behavior currently requires manual intervention for reports with mixed live and DirectQuery sources. Hopefully, future updates will improve integration across composite models with these different data sources.