Then there is the real life, outside of magic quadrants. You can take a look at other analysts, like BARC which takes the user perspective in account, this one Qlik always wins. However, if you are going to get value of a BI tool, you need to go through a few phases.
You need to understand, clean and connect to your source data. This is something you have to do regardless which tool you choose. With Qlik you aren’t forced to build a separate data warehouse.
After building you need to get your organization onboard and start using the apps, obviously the more user friendly they are the higher usage you’ll achieve. As Gartner has stated, visualizations are commodity, but there are differences. Tableau’s users love their graphs, while Qlik has their associative engine giving you insights you can’t get with other tools. And Power BI is just everywhere, integrated in Office 365.
This last part is the most important. There is a part of the analytic solution that once it’s built can remain static with some maintenance. But there is also an important part that needs to evolve and adapt to the changing business. Changes in your source system, new source systems, M&A bringing in new dimensions, new KPIs, all these are parameters to take in account – the key is what’s the sprint duration, is it 2–3 weeks or 2–3 months? If your data platform contains warehouses then it might be 2–3 months or even more. However this has started to change, with warehouses in the cloud and data warehouse automation tools. In some cases it can still be a challenge to simply make the people that build the extracts to fully understand the source systems and get the right data necessary for your analytics.
Just make sure you have a good understanding of your requirements on the agility of your analytics when selecting or further developing your data platform.