Using a large volume of data in Power BI without causing the reports to hang is a combination of good design, efficient data modeling, and optimizing the visuals. There are specific techniques that you can exploit.
1 . Use Import Mode Over DirectQuery
In Import Mode, Power BI pulls in a piece of the database and sticks it to its own engine, which is a very efficient database engine. This is usually faster than the DirectQuery mode, which performs a source database query every time the end user interacts with the report.
For most scenarios, the user can simply import the data rather than using DirectQuery, which is meant for situations where the user requires up-to-the-minute data at all times.
2. Optimize Your Data Model
Eliminate unneeded fields and limit the number of rows in the data set. The more data you get into the document, the more memory the Power BI consumes, which can decrease the processing speed.
Concentrate on obtaining only the key pieces of information that are essential for the analysis.
3. Leverage Data Aggregation and Summarization
If possible, try to find reasonable aggregations of the data to summarize before using it in Power BI. For example, when importing sales data, don't bring in every single sale; just the summary by year or by region.
Use Power Query to pre-aggregate and clean the data in the data preparation phase.
4. Shapes and images appropriation
At once, a landing page with many complicated graphs may reduce functionality. Limit the number of visuals used while creating content on the report page. Refrain from colors, shapes, and charts that require the viewer to sift through a large amount of information, such as a map and intricate thematic designs, rather than use large proportional designs and charts that simplify such designers. Use slicers or filters to limit the amount of data displayed at once, making it easier for Power BI to process.
5. Apply incremental data refresh
It is possible to refresh the dataset without having to do it for the entire dataset at a time. Still, it is also possible to incrementally refresh a report that primarily focuses on new or modified data added. This lightens the burden imposed on both one's device and Power BI. Such an approach is great for databases with massive data loads and a high frequency of change but with no need for a comprehensive refresh.
Concentrating on these points will help you ensure that your reports stay consistent for a long time despite the extensive data sets being handled.
