Incremental Refresh

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).

• Enabling/disabling incremental refresh again

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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 ,

What Happens When You Re-Publish a Power BI File with Incremental Refresh?

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.

So, What Happens if You Re-Publish?

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.

How to Re-Publish Without Replacing All Data

1. Minimize Re-Publishing from Desktop: Once the full data is loaded and the dataset is live in the service, avoid publishing again unless you're making non-structural updates, such as adjusting visuals or calculations.

2. Ensure Incremental Parameters Remain Intact:

• 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.

3. Use Deployment Pipelines (if available): If you’re using Power BI Premium, take advantage of Deployment Pipelines to move changes from development to production without disrupting the live dataset.

Best Practices

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

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Best Regards,
Nasif Azam