Essential checklist to keep your Power BI Solutions optimized. Part IV. Visualization Good Practices
This last article includes a list of best practices for data visualization.
– Use filters in your visualizations to reduce the amount of data that display: The more data a visual must display, the slower it will load, so apply filters in the Filters pane, or use Top N, to reduce the number of items displayed.
So, if your report is connected to a large data model and you do not apply any filtering, all the data will be loaded into memory and decompressed on each update, creating a huge memory demand.
– Only include the necessary number of visuals in your report: This will decrease the number of calculations that Power BI is performing when rendering your report. For example, you should use a multi-row card instead of using multiple single cards.
– Limit the use of slicers: Because they are visualizations, the underlying data will be updated every time the dashboard is refreshed, which could affect the performance.
– Use Microsoft-certified custom visuals: These have the Microsoft’s guarantee that these visual elements perform at their best, in addition have more options than non-certified ones.
– Avoid unnecessary interactions between visuals: Power BI automatically creates interactions between all the visuals on a page, which require high loading capacity that could slow down the loading of reports.
Therefore, make sure to eliminate the unnecessary interactions that Power BI creates by default.
– Use Performance Analyzer to Analyze the performance of your report elements: such as visuals and DAX formulas when users interact with them, and which consume the most resources.
✅ Excel Checklist
Download the Excel checklist at the following link: https://github.com/NuricBI/Checklist
In this article we reviewed how to improve and analyze the performance of your Power BI solutions in the different development layers:
✔ Data source.
✔ Data model.
✔ Data visualization.
You must be careful in each of them, because in whatever could be the cause that affects the final performance of the report.
Keep handy the excel file with the summarized list of best practices and recommended tools to analyze the performance of each phase of your solution.