A while ago I posted about loading Google Analytics data into QlikView (link [spanish]) using the java client. Today, I'm sharing with you an example about how to do the same with QVSource, the QlikView API connector.
QVSource is a third party software created by Industrial Codebox (the guys behind great QlikView related stuff) that enhances the connectivity power of QlikView, allowing us to connect to many different APIs such as Twitter, Facebook, Youtube, Sentiment APIs, Azure Marketplace and many others.
It runs in the background and each connector of QVSource connects directly to each API, retrieving the data locally so it can be loaded directly into QlikView and it can be associated with internal data of the company such as data stored in a datawarehouse, CRM, or ERP systems.
About the low level technical details, I think it would be reinventing the wheel if I explained here how to install QVSource and how to configure the Google Analytics connector because the QVSource doc page is really extensive and can get you through the process really quickly (and also offers many examples on how to use each connector). Visit the QVSource doc page here.
Like I did in my previous blog posts, I'm sharing with you a very simple QlikView app that will give you a glimpse on how to use QVsource with QlikView to load Google Analytics data and use the power of QlikView to 'master' the data.
In this app you can learn how to load the data into QlikView and analyze the most common metrics (visits, new visits, page views, time on site etc...) and dimensions (Geographical data, source, medium, keyword, ...).
|QlikView app example screenshot|
Download this QlikView example application here.
This is what you need to open the application:
- QlikView Desktop (get it from http://download.qlikview.com) with a valid license.
- A QlikView extension to visualize the map created by Brian Munz (get it and know more in this post: http://notas-bi.blogspot.com/2012/09/beautiful-maps-in-qlikview.html).
If you want to reload the app with your own Google Analytics data, you will need:
Feel free to comment and share this post.
I wish you all a Happy New Year!