You manage a Premium workspace that hosts a large dataset named FinanceModel. The dataset uses incremental refresh, and several thin reports were created in the Power BI service that connect live to FinanceModel. After adding new measures in Power BI Desktop, you must deploy the changes without replacing the dataset (so partitions are retained) and without altering any service-authored reports. Which deployment method should you use?
Publish the updated .pbix file from Power BI Desktop to the same workspace.
Use the Power BI service Quick Create experience to upload the updated file as a new item.
Use Tabular Editor or a similar tool to perform a metadata-only deployment through the workspace XMLA write endpoint.
Delete the existing dataset in the workspace, then import the modified .pbix file.
Deploying the revised model through the workspace's XMLA write endpoint (for example with Tabular Editor or ALM Toolkit) performs a metadata-only deployment. This updates the semantic-model definition in place, keeps existing incremental-refresh partitions, and leaves all reports-both the one embedded in the original .pbix and the service-authored thin reports-untouched. Republishing the .pbix replaces the entire dataset, forcing a full refresh and risking the loss of historical partitions (although thin reports would still connect). Deleting and re-importing or using Quick Create creates a new dataset, breaking existing reports.
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What is the purpose of the XMLA write endpoint in Power BI Premium?
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How does Power BI handle incremental refresh, and why is it important for large datasets?
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