Create your personalized Twitter Analytics Dashboard in Power BI in 10 minutes!

Create your own personalized Twitter Analytics Dashboard in Power BI

When I do Tweet the most? What day and hour do my Tweets receive the most interactions and impressions? With Power BI, these questions are very simple to answer. In this blog, you'll learn how to export your Twitter Analytics stats to use as a data source in a pre-built Power BI template provided here. Once you import the data into the template, you can explore many other interested metrics, such as the number of retweets, link clicks, profile clicks, and more.

The first step to creating this simple dashboard is to export your Twitter stats from

  1. Navigate to
  2. Click on "Tweets" on the top ribbon
  3. On the right, you'll see a button that defaults to the "Last 28 Days", change this to the past 90 days (maximum allowed), and click on "Export Data" to export the .csv

Next, download the Power BI Template from here and continue with the following steps:

  1. Download and open the attached TwitterAnalyticsDashboardTemplate.pbit file and open it in Power BI Desktop
  2. Click on "Edit Queries" in the top ribbon
  3. On the right side, you'll see "Applied Steps". Click on the gear icon next to the first step titled Source.
  4. Change the file path to point to your exported stats and click on OK
  5. Click "Close & Apply" in the top ribbon bar and your dashboard will be populated with your exported stats

Sam Lester (MSFT)


Comments (7)
  1. Great post and it was really easy to make. You only have to make sure that you change your Twitter Profile to English, because if you leave it to Dutch for example the Header of the export file is different and you need to do a lot of changes in the pbix file.

    1. Hi Erwin, thank you for the suggestion of changing the Twitter profile to English before exporting. I received another suggestion to update the source .csv file in the template to use Unicode (UTF-8) instead of the default 1252 West Europe, in order to display the correct encoding of special characters (Ü, Ä, Ö, etc.). I will do a bit of testing and update the template to better support additional languages. Thanks again for the feedback.

  2. b westphal says:

    Hi Sam, this truly was a 10 minute exercise, and I think it contains a lot of value. Thank you!!! But…
    The numbers I see in Twitter Analytics vs. the values that show in the exported data now in Power BI don’t match. Our social media people will see this and have no confidence in the data. I pulled the prior 28 days for instance and there were variances such as:
    167 link clicks in Twitter vs 125 in Power BI, 20 replies in Twitter vs 6 in Power BI, 151 likes in Twitter vs. 92 in Power BI. I tried this with 90 days of data and the prior calendar month and always found sizable variances.

    Am I doing or interpreting something incorrectly? I know social media data can have idiosyncrasies, is there something that I can explain to the users?

  3. sarabjit says:

    This is one of the best post i ever came for Power BI

  4. Aurel says:

    Hello Thanks for the post.
    How we can refresh automaticaly data with this method without download data every times.

    1. Hi Aurel, to get live stats in this dashboard, you would need to update the data source to a live data source as opposed to the exported analytics stats that I built it on. I don’t know if Twitter supports an API to programmatically access analytic data, but I’d start there first. If you can get access to the API, the data source of the PBI file can be changed to leverage the live API feed instead of the exported stats.

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