10 ways to optimise Power BI to build better dashboards

Power BI is a powerful tool for creating interactive dashboards that allow users to visualize and analyze complex data sets.

However, as dashboards become more complex and contain more data, the performance of the dashboard may start to suffer. Slow loading times and unresponsive visuals can lead to a poor user experience and hinder the effectiveness of the dashboard.

Fortunately, there are several ways to optimize Power BI dashboards for faster performance.

Here are 10 ways to do it.

1.Limit the number of visuals on a page. One of the simplest ways to improve dashboard performance is to limit the number of visuals on a page. A page with too many visuals can slow down the dashboard. It’s recommended to limit the number of visuals on a page to 6-8. If more visuals are required, consider splitting them across multiple pages.

2. Use simple visuals! Complex visuals like matrix tables and stacked charts can take longer to render. Use simple visuals like bar and line charts to improve performance. Simple visuals not only render faster but also make the dashboard easier to understand for the end-users.

3. Use efficient visuals: Some visuals require more processing power than others. For example, a clustered column chart requires more processing power than a stacked bar chart. Use the most efficient visual for the task at hand. A great resource to check for efficient visuals is the Power BI visualization gallery.

4. Use slicers and filters! Slicers and filters allow users to interact with the data on the dashboard. This reduces the amount of data that needs to be displayed. This can improve dashboard performance. However, avoid using too many slicers and filters, as they can also slow down the dashboard.

5. Use calculated columns instead of measures: Calculated columns are pre-calculated and stored in the data model… While measures are calculated on the fly. If a measure is used frequently, consider creating a calculated column instead to improve performance. This is because calculated columns are pre-calculated and can be stored in the data model. Whereas measures are calculated on the fly, which can cause a delay in loading time.

6. Use aggregations: Aggregations are pre-calculated summaries of data that can be used to improve performance. Use aggregations on large datasets or frequently used measures. This can improve the performance of the dashboard. This is because aggregations provide summarized data that can be quickly displayed.

7. Use DirectQuery instead of Import! DirectQuery connects to a live data source, while Import loads data into the data model. Use DirectQuery for large datasets or when near real-time data is required. DirectQuery can improve the performance of the dashboard by connecting directly to the data source! Rather than loading the data into the data model.

8. Optimize data model: Optimize the data model by removing unnecessary columns and relationships. This can improve performance and reduce the size of the data model. A smaller data model will load faster, and removing unnecessary columns and relationships will improve query performance.

9. Use Power Query to clean data: Power Query can be used to clean and transform data before loading it into the data model. Cleaning data before loading can reduce the size of the data model and improve performance. This can eliminate the need for complex calculations on the dashboard, as data is cleaned and transformed before it’s loaded.

10. Use the latest version of Power BI! The latest version of Power BI contains performance improvements and bug fixes. Always use the latest version of Power BI to ensure optimal performance. Microsoft releases new versions of Power BI frequently and keeping up with the latest version can ensure that any performance issues are addressed.