Hi, @Anonymous
The core of the problem seems to lie in the concurrent refresh capacity, rather than the total number of refreshes per day.
You can check the scheduled refresh times, and since you have multiple dashboards with frequent refresh schedules, consider staggering the refresh times to avoid peak times when multiple datasets may refresh at the same time. This helps reduce the risk of reaching capacity limits due to concurrent refreshes. For guidance on managing refresh schedules, see the following documents:
Refresh summaries for Power BI - Power BI | Microsoft Learn
Try to optimize your datasets and reports, and since each report includes a Power App component, make sure to optimize your dataset for refresh efficiency. This includes minimizing the size and complexity of the data model, as well as looking at any calculated columns or measures for optimization opportunities. For more details on optimizing Power BI reports, check out the following optimization documentation:
Optimization guide for Power BI - Power BI | Microsoft Learn
You can also monitor and adjust capacity settings, which is critical given the PPU environment and monitor capacity utilization and adjust settings as needed. While there is no explicit mention of the specific concurrent refresh limits of the PPU, efficient management of memory and resources is key. If you're using datastreams, consider adjusting your memory settings, especially if you have the enhanced compute engine enabled. The following links can be viewed:
Premium features of dataflows - Power BI | Microsoft Learn
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Best Regards
Yongkang Hua
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