Question

How to Import 500GB of Data into Power BI? – What’s the best strategy for handling massive datasets (500GB+) in Power BI? Direct Query, partitioning, or something else?

I need to import and analyze a massive dataset (500GB+) in Power BI. What is the best strategy for handling this efficiently? Should I use DirectQuery, partitioning, dataflows, or another approach to optimize performance and refresh times?

Answer 1

In Power BI, if you want to process 500 GB+ of data efficiently, you may want to consider:

DirectQuery: This is for real-time data connections and to avoid large imports that may slow down with a complex query.

Partitioning: Splitting the data into smaller segments (for example, time-based) for incremental refreshes will help improve performance and shorten refresh time.

Dataflows: These are used for cloud ETL processing and push heavy transformations to the Power BI service.

Aggregations: Summary tables will reduce the data size, which will, in turn, help improve performance and responsiveness for more detailed datasets.

Hybrid Model: A combination of imported data (for performance) and DirectQuery (for real-time data.)

Azure Synapse or SQL Server: Large datasets can be stored in scalable solutions and then connected to Power BI via DirectQuery or import.