Can you recommend any best practices for optimizing Power BI reports and dashboards for performance

[manoj_0911]

Hello Power BI Community,

As I delve deeper into Power BI report development, I'm eager to optimize the performance and efficiency of my reports and dashboards. Could you please share any best practices or strategies for achieving optimal performance in Power BI? Whether it's related to data modeling, visualization design, or query optimization, I'm open to any insights or tips you may have.

Thank you for sharing your expertise.

Best regards,
Manoj Prabhakar

[danextian · Accepted solution]

Hi @manoj_0911 

Here are just some:

• Use a separate Dates table to facilitate time intelligence calculations
• Split a Datetime column into Date and Time columns for lesser cardinality.
• Preference over thin vs wide tables
• Filter only the rows and select only the columns needed.
• Custom columns in M for those that do not involve scanning a table like concatenating columns, adding columns, etc. DAX if it involves scanning a table like getting the sum of several rows based on the unique values in a colums.
• use performance optimization tools like Tabular Editor and DAX studio - https://learn.microsoft.com/en-gb/training/modules/use-tools-optimize-power-bi-performance/ 

[Idrissshatila · Accepted solution]

Hello @manoj_0911 ,

check this blog, it covers evey aspect that you could optimize.

https://www.linkedin.com/pulse/power-bi-optimization-framework-ahmad-chamy-nensf%3FtrackingId=o6Vf8R...

[Anonymous · Accepted solution]

Hi @manoj_0911 ,

You can refer the following methods to get it:

1. Optimize your data model: One of the most important factors in Power BI performance is the quality of your data model. Make sure your data is clean and well-organized, and that you're using the appropriate data types and relationships. You can also use features like calculated columns and measures to optimize your data model and improve performance.

Optimization guide for Power BI - Power BI | Microsoft Learn

2. Use DirectQuery or Live Connection: If you're working with large datasets, consider using DirectQuery or Live Connection to connect to your data source instead of importing the data into Power BI. This can help improve query performance and reduce the size of your Power BI file.

Use DirectQuery in Power BI Desktop - Power BI | Microsoft Learn

What's the difference between live connections and DirectQuery? - Power BI | Microsoft Learn

3. Use visuals sparingly: While Power BI offers a wide range of visualizations, using too many visuals can slow down your report. Instead, focus on using the most relevant and impactful visuals to convey your message.

4. Use filters and slicers: Filters and slicers can help improve performance by reducing the amount of data that needs to be loaded into your report. Use them strategically to allow users to interact with your data without overwhelming the report.

5. Use the Performance Analyzer: Power BI includes a Performance Analyzer tool that can help you identify performance bottlenecks in your report. Use this tool to identify areas where you can optimize your report and improve performance.

Use Performance Analyzer to examine report element performance (can see and record logs that measure how each of your report elements performs when users interact with them, and which aspects of their performance are most (or least) resource intensive.)

In addtion, you can refer the following links to optimize your DAX formulas:

For DAX:

DAX Best Practice Guide

Optimizing DAX Video Course

Best Regards

[Idrissshatila · Accepted solution]

Hello @manoj_0911 ,

check this blog, it covers evey aspect that you could optimize.

https://www.linkedin.com/pulse/power-bi-optimization-framework-ahmad-chamy-nensf%3FtrackingId=o6Vf8R...

[danextian · Accepted solution]

Hi @manoj_0911 

Here are just some:

• Use a separate Dates table to facilitate time intelligence calculations
• Split a Datetime column into Date and Time columns for lesser cardinality.
• Preference over thin vs wide tables
• Filter only the rows and select only the columns needed.
• Custom columns in M for those that do not involve scanning a table like concatenating columns, adding columns, etc. DAX if it involves scanning a table like getting the sum of several rows based on the unique values in a colums.
• use performance optimization tools like Tabular Editor and DAX studio - https://learn.microsoft.com/en-gb/training/modules/use-tools-optimize-power-bi-performance/