Loading Qonnections 2015 Instagram Posts Into Qlik Sense (Or QlikView)

In this post we will demonstrate using the new Web Edition of QVSource to load data from Instagram into Qlik Sense Desktop.

The QVSource Web Edition is currently in private beta but should be available for general (beta) download in June 2015. We are also currently hosting an invite only cloud hosted instance of QVSource Web Edition which a number of users are already testing out the new version with. If you would like to be considered for access to this please fill out this form.

NOTE: You can also try this out using the current QVSource Desktop Edition. Whichever version of QVSource you are using, when using Qlik Sense just remember that at present you will first need to make this minor config change in order to allow load requests from arbitrary URLs.

First of all we fire up QVSource and open the Instagram connector. We ensure we are authenticated with Instagram and then select the SearchForTags table and enter ‘qonnections’ in the Tag field. There are (at time of writing) 303 results for ‘qonnections’:

We can see that there are a few Instagram tags being used in relation to Qonnections, the most popular one being simply 'qonnections'. We can now go to the MediaByTag table and make sure that this tag name is entered as the tag to find Instagrams for and then run the table.

We then select the Qlik Sense tab and copy the script to the clipboard:

Now we fire up Qlik Sense Desktop, create a new app and open the data load editor:

We paste in the script, and click load data:

And run the reload:

Note that we do not necessarily get back as many results as suggested in the earlier table as the SearchForTags table above shows counts including images which are private or might have subsequently been deleted.

We then return to the app overview and create a new sheet:

We edit the sheet and drag a bar chart in:

Then add the dimension username:

...and a measure of count(id):

We then limit to the top 10:

...and complete the edit, giving us the top 10 posters:

We now create a new sheet and add a table with dimensions for user name and link; and a measure for sum(likes count):

We can then sort by likes (descending) to see the most liked posts and poster:

We click ‘done’ to view the results:

Now we create a new sheet and add a bar chart with create time (utc qlik date) as dimension and count(id) as measure. This can be sorted by the dimension (date) first and saved, showing the peaks in posting media around the annual Qonnections conference:

This demonstrates just how easy it is to pull data from instagram and quickly extract meaningful patterns and trends. This is just a simple example, in a real world example we might want to write QlikView/Qlik Sense load script to loop through a number of different tags which were used during the event. We could also extract a great deal more data such as comments and likes using the many other tables which the connector supports.

You will find a more complete example for QlikView over on our GitHub Page - note that although this is for QlikView the load script should also work fine in Qlik Sense giving you the same data model to build your user interface on top of.

You can request a fully functional free trial of QVSource from our and try out the 35+ Connectors it supports with QlikView or Qlik Sense.

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