In managing Power BI datasets with live and import data connections, you need to strike a balance between data freshness and performance. Here are a few recommendations that will assist you in this endeavor.
Use a Hybrid Dataset Strategy: Employ a hybrid approach to your dataset by categorizing it according to the frequency of updates needed. For tables or sources in need of up-to-the-minute or almost real-time provided data, DirectQuery or live connection measures should be used. This is to ensure these particular sections of your data update with the latest input. Where real-time information is not a critical requirement, such as in those cases of historical datasets or reference data, the data should be imported. This mode can considerably enhance performance as data is stored in the memory of Power BI, eliminating the long query processes.
Optimize Data Model for Performance: The use of live connections implies the use of the data source, which would then mean that such connections would compromise the report performance if the queries are handled complexly and large volumes of data are involved. Clean up your model - delete columns and rows that are not needed, and use row-level filtering before the data is loaded to lessen the impact of the data load. Employ aggregations as much as possible - Power BI can be configured to import mode where only the high-level views aggregated data is imported and detailed data accessed via Direct Query when the user needs the specific information, thus cutting down on time taken, balancing the need for data in real-time and performance.
Scheduled Refresh and Incremental Refresh Policies: When dealing with imported data, plan the scheduled refreshes to take place during off-peak hours to prevent performance degradation during peak operational hours. Implement incremental refresh to handle large tables, which only target updating new or modified data without going through the processes of loading the whole dataset; hence, time and resources are conserved. For DirectQuery tables, the refresh settings should be implemented with caution—tweaking the settings not only for the user's real-time requirement but also for the system's stress. It is preferred that the less important data sets have minimal refresh rates while the important data sets are refreshed at the rate that meets the business requirements.
This allows Power BI to be used to its full capability by sticking to real-time when it is really required, but for the rest, it opted for performance caching.
