Incremental Refresh - First scheduled refresh duration and cached data usage

Hi Anonymous 

When you publish a Power BI dataset with Incremental Refresh (IR) enabled, it’s important to understand how the first refresh in the Power BI Service behaves. Even though you already loaded six months of data in Power BI Desktop and enabled IR before publishing, the Service doesn’t directly use the cached data stored in your PBIX file. Instead, during the first refresh after publishing, Power BI performs a full partition refresh to create and store the historical and incremental partitions in the Service environment (essentially rebuilding the dataset structure for incremental logic). This means it will query all six months (the historical range) from Oracle again — not just the new one-day partition. As a result, the first refresh often takes nearly as long as your initial load in Desktop, and it’s completely normal for it to run for several hours on large datasets. Once this initial refresh is successfully completed, Power BI will maintain the partition structure, and subsequent refreshes will only query the incremental (1-day) range, making them much faster.

For best performance with Oracle sources, it’s recommended to ensure that your partitioning column (used for incremental logic) is indexed and filterable so Power BI can efficiently apply query folding. Also, consider performing the first refresh during off-peak hours or using Power BI Premium capacity with higher resource allocation to prevent timeouts. In summary: yes, the first scheduled refresh reprocesses all partitions, yes it’s normal for it to take several hours, and future refreshes will be much quicker once the incremental structure is established.