I could not find user experiences or reviews to determine the Tandem Power BI Connector's performance with large datasets, which is very important from the viewpoint of operational effectiveness and reliability when dealing with high-volume data. If you are considering using this connector in your project, I suggest you contact the vendor or speak to others who have implemented it in similar settings.
In the meantime, here are some suggestions for enhancing Power BI performance with larger datasets:
Incremental Refresh: Implementing incremental refresh allows Power BI to refresh only new or changed data, drastically reducing refresh time and enhancing performance.
Aggregations: With aggregations, you can increase performance by summarizing detailed data into aggregate tables that allow Power BI to access smaller aggregated tables instead of scanning the whole dataset.
Direct Query Mode: For real-time data access and handling large datasets, Direct Query leaves the data in the source system and queries it in real-time to ensure current data access while minimizing the need to load large volumes into Power BI.
These strategies enable you to effectively deal with large datasets in Power BI, assuring efficient performance and scalability.
