Question

What strategies can I use to handle large datasets without slowing down my Power BI reports?

To handle large datasets without slowing down Power BI reports, strategies like efficient data modeling, using aggregations, optimizing queries, and employing DirectQuery or data reduction techniques are crucial for maintaining performance.

Answer 1

If you want to view a Power BI Report with Large Datasets in it without compromising the Slow Performance of the Report, Employ the Following Strategies:

Data-extraction methods: First, transfigure only the data needed into Power BI. Then, Deploy filters at the source to reduce the dataset's size. For instance, if I am working with sales data and want to analyze sales by region, I would extend the data limitation to years when such areas were available. This would remove a lot of data that Power BI would have dealt with, hence enhancing the speed of report generation.

Optimized data model: Logically structure your data by constructing a star schema as opposed to using a flat table design. A star schema is one where the fact tables, such as sales transactions, are kept separate from the dimension tables that contain information about customers and products. This design helps in enhancing the reports because the publication of data processing is faster in Power BI.

Streamlined DAX expressions: Do not attempt to prevent the rational use of time for unnecessary calculations done in DAX that are not helpful. Instead, do that in the data source whenever you can. If one needs to calculate sales as of date for numerous periods, do not – within Power BI – create a DAX measure; rather, add a column in the source database.

When used together, all the above strategies guarantee that reports created in Power BI will work with heavy datasets without any performance issues.

Answer 2

In Power BI, to deal effectively with large datasets without hampering the performance of reports, concentrate on the proper data modeling practices by eliminating the unimportant columns and rows and applying star schema for ease. Use Aggregates to reduce the processing burden and display the data in more summarized sections.
 Enhance efficiency in Power Query actions by optimizing and ensuring that heavy transformation processes are not executed after the data load. If real-time access is required, use DirectQuery or, if utilizing the pulled data, load only the required data by applying data reduction strategies such as filters or incremental refreshing. These approaches present better performance and shorter loading periods for the reports.