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To optimize performance in large data sets, Power BI developers should employ techniques like using DirectQuery or composite models judiciously to minimize data import. Reducing the number of visuals and using aggregations instead of detailed data in reports can significantly improve speed. It’s also crucial to avoid complex DAX calculations that can slow down performance and to optimize data models by removing unnecessary columns and relationships. Using parameters to filter data at the source and employing measures like incremental data refresh further enhance performance. By implementing these strategies, developers ensure that reports remain responsive and efficient, even with large data volumes.
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