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Krushnab85
Helper I
Helper I

Performance Analyzer Doubt

I am using performance analyser to analyse the report performance, but after recording it and export it to the JSON file and using that JSON into the power bi i dont  get the tab/pages names so i can go through the particular page who is taking more time to load...any idea how to find particular page load time?
In the dax studio also the name of the tabs/Pages are not displayed.

2 ACCEPTED SOLUTIONS
rajendraongole1
Super User
Super User

Hi @Krushnab85 -Performance Analyzer doesn't show page names directly in the JSON file, best approach is to run the Performance Analyzer separately for each page, export the results, and compare them.Repeat this process for each page separately, so each JSON file corresponds to one page.

Though DAX Studio does not directly show page names but to identify the  slow queries and optimize them we can use it.

 

Ref:

Solved: Performance analyzer - Microsoft Fabric Community

Solved: Performance Analyzer / Dax Studio - Microsoft Fabric Community

 

Hope this information helps.

 

 

 

 





Did I answer your question? Mark my post as a solution!

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View solution in original post

suparnababu8
Super User
Super User

Hi @Krushnab85 

To analyze the performance of specific pages in your Power BI report and identify which pages are taking more time to load, you can follow these steps:

Using Performance Analyzer in Power BI Desktop

  1. Record Performance:

    • Open your report in Power BI Desktop.
    • Go to the View tab and click on Performance Analyzer.
    • Click Start Recording and then navigate through the pages of your report.
    • After you’ve navigated through the pages, click Stop Recording.
  2. Export Performance Data:

    • Click on Export to save the performance data as a JSON file.

Analyzing the JSON File

The JSON file contains detailed performance data, but it doesn’t directly include page names. To map the performance data to specific pages, you can follow these steps:

  1. Open the JSON File:

    • Use a text editor or a JSON viewer to open the exported JSON file.
  2. Identify Visual Load Times:

    • Look for entries under "visuals" which contain "displayName" and "duration" fields. These entries represent the load times for individual visuals.
  3. Map Visuals to Pages:

    • Unfortunately, the JSON file does not directly include page names. However, you can manually correlate the visuals to pages by noting the order in which you navigated through the report during the recording.

Using DAX Studio

DAX Studio can help you analyze query performance, but it doesn’t provide page names either. However, you can use it to identify slow-running queries and then manually correlate them to the visuals and pages in your report.

Alternative Approach: Using Bookmarks

  1. Create Bookmarks:

    • Create bookmarks for each page in your report.
  2. Record Performance with Bookmarks:

    • Use the Performance Analyzer to record performance while navigating through the bookmarks. This way, you can more easily correlate the performance data to specific pages.

Summary

While the JSON file from Performance Analyzer and DAX Studio do not directly provide page names, you can manually correlate the performance data to specific pages by noting the order of navigation or using bookmarks. This approach requires some manual effort but can help you identify which pages are taking more time to load.

View solution in original post

2 REPLIES 2
suparnababu8
Super User
Super User

Hi @Krushnab85 

To analyze the performance of specific pages in your Power BI report and identify which pages are taking more time to load, you can follow these steps:

Using Performance Analyzer in Power BI Desktop

  1. Record Performance:

    • Open your report in Power BI Desktop.
    • Go to the View tab and click on Performance Analyzer.
    • Click Start Recording and then navigate through the pages of your report.
    • After you’ve navigated through the pages, click Stop Recording.
  2. Export Performance Data:

    • Click on Export to save the performance data as a JSON file.

Analyzing the JSON File

The JSON file contains detailed performance data, but it doesn’t directly include page names. To map the performance data to specific pages, you can follow these steps:

  1. Open the JSON File:

    • Use a text editor or a JSON viewer to open the exported JSON file.
  2. Identify Visual Load Times:

    • Look for entries under "visuals" which contain "displayName" and "duration" fields. These entries represent the load times for individual visuals.
  3. Map Visuals to Pages:

    • Unfortunately, the JSON file does not directly include page names. However, you can manually correlate the visuals to pages by noting the order in which you navigated through the report during the recording.

Using DAX Studio

DAX Studio can help you analyze query performance, but it doesn’t provide page names either. However, you can use it to identify slow-running queries and then manually correlate them to the visuals and pages in your report.

Alternative Approach: Using Bookmarks

  1. Create Bookmarks:

    • Create bookmarks for each page in your report.
  2. Record Performance with Bookmarks:

    • Use the Performance Analyzer to record performance while navigating through the bookmarks. This way, you can more easily correlate the performance data to specific pages.

Summary

While the JSON file from Performance Analyzer and DAX Studio do not directly provide page names, you can manually correlate the performance data to specific pages by noting the order of navigation or using bookmarks. This approach requires some manual effort but can help you identify which pages are taking more time to load.

rajendraongole1
Super User
Super User

Hi @Krushnab85 -Performance Analyzer doesn't show page names directly in the JSON file, best approach is to run the Performance Analyzer separately for each page, export the results, and compare them.Repeat this process for each page separately, so each JSON file corresponds to one page.

Though DAX Studio does not directly show page names but to identify the  slow queries and optimize them we can use it.

 

Ref:

Solved: Performance analyzer - Microsoft Fabric Community

Solved: Performance Analyzer / Dax Studio - Microsoft Fabric Community

 

Hope this information helps.

 

 

 

 





Did I answer your question? Mark my post as a solution!

Proud to be a Super User!





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