Hi Jurien, I think the place to start is with the need for information - "Who isn't getting information they need and why?" Not everybody who needs information is an analyst or a data scientist. If tool selection is focused only on “techies”, the consumers will still be relying on someone to create content for them. Or worse yet, not getting information at all because the bottleneck to get information still exists.
I worked at Cognos for years and PowerPlay was extremely popular with consumers (non-technical people) because they could explore data more broadly. Techies like you essentially gave the consumers a sandbox to play in - a safe one, where they couldn't get into trouble. Of course, Qlik is far more sophisticated than PowerPlay but the idea of exploring data more broadly is consistent.
Comparing Qlik to these other tools feels like comparing Impromptu to PowerPlay. They are fundamentally different. The evaluation criteria seems to be set up for a query-based tool geared to business analysts who will "author" content. If you were to set up the criteria around an exploration tool for the consumer the results would look vastly different.
I also question some of the scores and categories. For example:
Data modelling / blending. Blending and joining are very different. Blending is on summarized data where joining is on raw data. Order of precedence can be critical in obtaining correct results so if your tool can't "join" multiple sources, there are cases where you will not get correct results. Can the other 2 vendors really deliver content that "joins" data from 3, 5 or 10 data sources? Customers would have to buy something like Talend, Alteryx or another solution to stage the data first.
Scalability. This is a very broad term. It could mean scaling to multiple users, lots of data, lots of dimensions, lots of servers, etc. It's doesn't consider static vs dynamic content or performance. If you are just referring to data volumes, then it is incorrect to give Qlik a lower score. Qlik's direct discovery capability allows you to live query any volume of data from the database. If you are referring to in-memory data volumes, Qlik would be the hands-down winner.
Data Load Time. This an odd measurement because of the fundamental difference in the tools. The other two load a query or two. The data is broad and highly summarized or very narrow and deep. Exploring data (getting to related information) requires a separate piece of content or a new query. Qlik offers exploration across broad and deep information in a single app. How long would it take the other two tools to load billions of records across 30 dimensions of information? And then how fast would it perform as consumers filter through the results?
Your point 4 is spot on and should probably be towards the top of your analysis. End users don't know these tools - and they don't want to learn how to create content to answer their questions. If it's hard to use or hard to find information, they will not use the tool. But adoption is not a factor with BI specialists or business analysts. They will figure out how to use whatever tool is selected. Any of these tools do a decent job of satisfying the needs of the business analyst/techie. But I would suggest that Qlik Sense gives you - the techie - far better ability to satisfy the information needs of those who will never author content.
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