Join us at FabCon Atlanta from March 16 - 20, 2026, for the ultimate Fabric, Power BI, AI and SQL community-led event. Save $200 with code FABCOMM.
Register now!The Power BI Data Visualization World Championships is back! Get ahead of the game and start preparing now! Learn more
Hello,
If i loaded the data for last 2 weeks in power bi desktop , then applied incremental refresh to pull the data in the service from 2020 so i have the full data now in the service .
My question is
if i changed something in the desktop report and re-published it again to the service , will it override the full data report with the 2 weeks ? and i have to refresh the whole model again?
if yes
how i can re-publish any changes with out affecting the full data in the service
thank you
Solved! Go to Solution.
Hi @ahmedshalabyy12,
No, re-publishing the .pbix file will not override the full historical data already stored in the Power BI Service as long as:
You don’t change the partition logic or the incremental refresh policy (e.g., "last 2 years store, refresh last 2 weeks").
You don’t disable or modify the parameters used for partitioning (like RangeStart / RangeEnd).
🌟 I hope this solution helps you unlock your Power BI potential! If you found it helpful, click 'Mark as Solution' to guide others toward the answers they need.
💡 Love the effort? Drop the kudos! Your appreciation fuels community spirit and innovation.
🎖 As a proud SuperUser and Microsoft Partner, we’re here to empower your data journey and the Power BI Community at large.
🔗 Curious to explore more? [Discover here].
Let’s keep building smarter solutions together!
@ahmedshalabyy12 - Yes, hitting publish from power bi will do exactly that. You have several options to prevent this.
1) Enable the XMLA Endpoint and use ALM Toolkit to do a metadata only update.
2) Enable the XMLA Endpoint and use Tabular Editor 2 to deploy the model changes.
https://learn.microsoft.com/en-us/power-bi/enterprise/service-premium-connect-tools
3) Or (and probably the best option) you can make use of the new Save to One Drive and Sharepoint functionality, here's more info: https://www.youtube.com/watch?v=FtsYYZpH6S4
If I answered your question please mark my post as the solution, it helps others with the same challenge find the answer!
Hey @ahmedshalabyy12 ,
When you use Incremental Refresh in Power BI Desktop, you typically load a recent sample of the data like the last 2 weeks for development purposes. Once you publish this file to the Power BI Service and run a refresh, the service loads the full dataset as defined by your incremental refresh policy (e.g., from 2020 onward). The service creates data partitions in the background to manage historical and recent data efficiently. However, Power BI Desktop doesn’t retain these partitions. It only holds the sample data you loaded for development.
If you publish the same .pbix file again after the full dataset is already in the service:
The dataset definition is overwritten, but the existing data in the service remains intact unless the schema or logic has changed.
On the next refresh, Power BI Service will process data according to your incremental settings.
As long as the incremental refresh setup and partitioning logic remain unchanged, it will not reload the entire dataset only the portion defined as "incremental" will be refreshed.
Keep the RangeStart and RangeEnd parameters in place.
Do not change the filtering logic that uses these parameters in Power Query.
This ensures that the existing partitions in the service remain valid after the re-publish.
Re-publish with no model or data query changes --> Safe
Re-publish with changes to data structure or M code --> Risk of triggering a full refresh
Refresh from Power BI Service after re-publish --> Incremental refresh works if setup is untouched
Use Deployment Pipelines --> Better control and safer updates
For Detailed Information:
Configure Incremental Refresh and Real-Time Data in Power BI
Incremental refresh and historical data
Deployment pipelines in Power BI
Best practices for using incremental refresh
Guy in a Cube - Power BI Incremental Refresh
SQLBI - Understanding Incremental Refresh
If you found this solution helpful, please consider accepting it and giving it a kudos (Like) it’s greatly appreciated and helps others find the solution more easily.
Best Regards,
Nasif Azam
Hey @ahmedshalabyy12 ,
When you use Incremental Refresh in Power BI Desktop, you typically load a recent sample of the data like the last 2 weeks for development purposes. Once you publish this file to the Power BI Service and run a refresh, the service loads the full dataset as defined by your incremental refresh policy (e.g., from 2020 onward). The service creates data partitions in the background to manage historical and recent data efficiently. However, Power BI Desktop doesn’t retain these partitions. It only holds the sample data you loaded for development.
If you publish the same .pbix file again after the full dataset is already in the service:
The dataset definition is overwritten, but the existing data in the service remains intact unless the schema or logic has changed.
On the next refresh, Power BI Service will process data according to your incremental settings.
As long as the incremental refresh setup and partitioning logic remain unchanged, it will not reload the entire dataset only the portion defined as "incremental" will be refreshed.
Keep the RangeStart and RangeEnd parameters in place.
Do not change the filtering logic that uses these parameters in Power Query.
This ensures that the existing partitions in the service remain valid after the re-publish.
Re-publish with no model or data query changes --> Safe
Re-publish with changes to data structure or M code --> Risk of triggering a full refresh
Refresh from Power BI Service after re-publish --> Incremental refresh works if setup is untouched
Use Deployment Pipelines --> Better control and safer updates
For Detailed Information:
Configure Incremental Refresh and Real-Time Data in Power BI
Incremental refresh and historical data
Deployment pipelines in Power BI
Best practices for using incremental refresh
Guy in a Cube - Power BI Incremental Refresh
SQLBI - Understanding Incremental Refresh
If you found this solution helpful, please consider accepting it and giving it a kudos (Like) it’s greatly appreciated and helps others find the solution more easily.
Best Regards,
Nasif Azam
@ahmedshalabyy12 - Yes, hitting publish from power bi will do exactly that. You have several options to prevent this.
1) Enable the XMLA Endpoint and use ALM Toolkit to do a metadata only update.
2) Enable the XMLA Endpoint and use Tabular Editor 2 to deploy the model changes.
https://learn.microsoft.com/en-us/power-bi/enterprise/service-premium-connect-tools
3) Or (and probably the best option) you can make use of the new Save to One Drive and Sharepoint functionality, here's more info: https://www.youtube.com/watch?v=FtsYYZpH6S4
If I answered your question please mark my post as the solution, it helps others with the same challenge find the answer!
Hi @ahmedshalabyy12,
No, re-publishing the .pbix file will not override the full historical data already stored in the Power BI Service as long as:
You don’t change the partition logic or the incremental refresh policy (e.g., "last 2 years store, refresh last 2 weeks").
You don’t disable or modify the parameters used for partitioning (like RangeStart / RangeEnd).
🌟 I hope this solution helps you unlock your Power BI potential! If you found it helpful, click 'Mark as Solution' to guide others toward the answers they need.
💡 Love the effort? Drop the kudos! Your appreciation fuels community spirit and innovation.
🎖 As a proud SuperUser and Microsoft Partner, we’re here to empower your data journey and the Power BI Community at large.
🔗 Curious to explore more? [Discover here].
Let’s keep building smarter solutions together!
@grazitti_sapna - this is incorrect, because the pbix file only has 2 weeks worth of data in it, whereas the server has data loaded from 2020 onwards.
So yes, hitting publish will overwrite this data. Admittedly the next refresh will replace it again, but as I have listed, there are better options to ensure there is no data loss for any period.
The Power BI Data Visualization World Championships is back! Get ahead of the game and start preparing now!
| User | Count |
|---|---|
| 46 | |
| 42 | |
| 34 | |
| 31 | |
| 21 |
| User | Count |
|---|---|
| 133 | |
| 126 | |
| 95 | |
| 80 | |
| 65 |