Yammer Analysis using PowerBI

Author by Concurrency Blog

Today I’m going to show you how to analyze any company’s yammer trends using powerBI. The beauty of powerBI is the ‘Refreshable Database Query’ feature of PowerQuery. I know the terms that I’m using may sound a bit complicated. But, you will be amazed when I show you how to analyze yammer activities in just a few clicks.

So, what is ‘refreshable query’? It’s a very simple concept. The sample excel file which I am going to provide here will help you to analyze the entire yammer activities in just ONE click. Unbelievable? That’s PowerBI for you! You just have to work hard once to create the sample file and use the ‘REFRESH’ button to analyze the yammer trends forever. You can download the sample file by clicking HERE.

Now, once you download this sample file, go to https://yammer.azurewebsites.net. You will now be connected to the windows azure service of Microsoft that hosts the Yammer Export Processor.yammer1

Now, when you see this screen, click on the Yammer icon in the blue colour to login. Once you login, you will see a ‘Terms & Conditions page. Check mark I agree the terms and conditions to proceed further to 'select network'.


If you don’t have admin rights then you cannot import the yammer data. Please contact your network admin to grant you the network admin rights. You have to be a verified admin to successfully import the data using Yammer Export Processor.

Next it will ask us the timeframe of the export. So, basically you have to put a start date to export all the data from the specified time period. The screen should look something likeyammer3

You have to specify some of the options that you want to export. You can select the data you want to analyze by ticking the corresponding checkbox. Please exclude the ‘Process message sentiment’ checkbox from your analysis. You can export interesting data like mentions, time between the messages, follows, shares, likes, private/ public group messages.yammer4

You can see that I haven’t selected the ‘Process message sentiment here as it requires API key which is out of the scope of our sample file. Next, you get a chance to review the data.yammer5

Click on the Start Export button and you will now see a status screen. The progress will be seen and it may take a lot of time depending on the size of the company. For large companies, it may even take days to complete the export. Once the export is complete, locate the folder where all the exported data files are downloaded.

The next step is perhaps the most important step. You have to create a new folder in your ‘C drive’ and name it ‘Exports’. Then you have to open the sample file which you downloaded initially. You can download the sample file again by clicking below.


Now, open the sample file and get ready for some magic. The sample file has a model made in PowerPivot and all you have to do is click ‘REFRESH’ against all the data sources we exported.

You must have PowerPivot installed as an excel add-in to continue further and click on REFRESH dropdown. If you don’t have powerpivot installed then please go to the link mentioned below and download powerpivot. It is a free add-in provided by Microsoft.


Once, you have the PowerPivot, open the sample file and click on PowerPivot tab on the top right corner to open the powerpivot window. Now, with just a click of button, you will be able to populate all the graphs of the sample file with your company’s data. This magic button is called ‘Refresh All'. It is located at the top center of the screen. Click on the ‘Refresh’ dropdown list at the top center of the screen and click on ‘Refresh All’. This can take a long time especially if you have a large network.


The process is complete and you can go to individual excel sheets at the bottom left to slice and dice the graphs.

I have created a detailed report on yammer analysis by using this sample file. I will be glad to discuss how I analyzed the data using this sample file. Please comment for more information or connect with me on LinkedIn. Have a great day and see you again next week!


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