Are you trying to improve the performance and security of enterprise-grade Power BI implementations? Well, you can do that by implementing the best practices of Power BI. There are numerous Power BI based dashboards that are used by thousands of enterprise users every day in order to drive operations as well as marketing. This article intends to introduce you to 11 best practices of Power BI.
1. Limit the visuals in dashboards and reports
Do you know what slows the report performance? The Microsoft Power BI performance best practices highlight that placing many visuals in a single report is responsible for it. This is what you need to do in order to limit the number of visuals in dashboards and reports:
- Limit to a minimum of eight widget visuals in every report page and keep the grids to a minimum of one in every page
- The pages should be limited to no more than 30 points (cards: 1, gauges: 2, charts: 3, maps: 3, grids: 5)
- Keep the tiles limited to no more than 10 per dashboard.
2. Remove unnecessary interactions between visuals
Want to know the secret of improving Power BI report performance? Here’s a hint! You can make that possible by removing unnecessary interactions between visuals. This is possible because of the reason that all visuals on a report can interact with one another by default. The interactivity should be controlled and modified for optimal performance.
Further, you can reduce the number of queries fired at the backend and improve report performance by disabling unwanted interactivity.
3. Enable Row-Level Security (RLS)
Power BI only imports the data that the user is authorized to view, with RLS that restricts user access to certain rows in a database depending on the characteristics of the user executing a query.
But how to attain substantial performance gains? You can enable this by combining Power BI roles with roles in the backend. Moreover, you need to test all roles prior to rolling out to production.
4. Use Microsoft AppSource certified custom visuals
The Power BI certified custom visuals are verified by Microsoft to have robust as well as well-performing code. These AppSource visuals have passed rigorous quality testing and are the only custom visuals that can be viewed in Export to PowerPoint and email subscriptions.
5. Avoid using hierarchical filters
Yes, that’s what you need to do when you observe poor performance in Power BI. Are you getting bothered by high page load times while using hierarchical filters? Try this! Remove the hierarchical filters. Experience an enhanced performance in Power BI by using multiple filters for the hierarchy.
6. Categorize the data for Power BI reports
One of the best practices in Power BI is to provide data categorization for the Power BI reports (HBI, MBI, LBI). The Power BI data classification enables you to raise user awareness about the security level that is required to be used. This also helps you to understand the way reports should be shared inside as well as outside the organization.
The categories can be listed as:
- HBI or High Business Impact data, that requires users to get a policy exception to share the data eternally.
- LBI or Low Business Impact as well as MBI or Medium Business Impact, that do not require any exceptions.
7. Use the On-premises data gateway
It is suggestible as well as one of the best practices to use on-premises data gateway instead of Personal Gateway for it takes data and imports it into Power BI. But why Enterprise Gateway? It is more efficient while you work with large databases as Enterprise Gateway imports nothing.
8. Use separate Power BI gateways for “Direct Query” and “Scheduled Refresh”
As you know that using the same gateway for Scheduled Data Refresh and Live Connection slows down the Live Connection performance when the Scheduled Data Refresh is active. It is suggestible for you to create separate gateways for Live Connection and Scheduled Refresh to avoid such issues.
9. Test each custom visual on a report for ensuring fast report load time
The Power BI team doesn’t thoroughly test the custom visuals that are not certified. So, while handling large datasets or complex aggregations, the custom visuals might perform poorly.
What should you do when the chosen visual performs poorly? You can overcome the issue by using an alternative visual. Ensure fast report load time by testing each custom visual on a report for performance.
10.Limit complicated measures and aggregations in data models
Increase the likelihood of improved performance by pushing calculated columns and measures closer to the source wherever possible. Moreover, you need to create calculated measures instead of calculated columns while using star schema in order to design data models.
11. Import what’s necessary
Why do you need to import entire datasets, when you can keep the model as narrow and lean as possible by importing only necessary fields. Power BI works on columnar indexes where longer and leaner are preferred.
To conclude
The above are the top 11 best practices that you need to understand to smoothly approach with all the Power BI reporting as well as analysis. Further, it is recommended for you to follow each of these best practices in every piece of work that you do inside of Power BI. You should also gain an understanding of how the work is done as well as try to incorporate them into your own work. On a concluding note, wish you all the best for your successful Power BI developments with these best practices by your side!
