Great article, these were things that I knew zero about before now, but I have 2 questions about your article:
The challenge this approach doesn’t resolve is: what happens if the questions the users are asking change?
Isn't this the inherent challenge of Data Warehousing? Isn't that the thing that separates the men/women from the boys/girls? I am not a seasoned expert by any means, but I hope to be one day. Heck, I'm only taking my first swing at designing a data warehouse with the BI team that I'm on, but, that seems to be the elephant in the room, that you are attempting to (at the end of a rigorous process) create a system that will "be able to answer the questions that haven't been thought of yet". This question is not in an argumentative tone, but more to make sure that I haven't missed something. If we had all decided that the changing questions in the future would be unanswerable once we built a DW, then maybe I am not pursuing the most effective solution.
2. Isn't the Big Data arena (including this data lakes concept) really more suited for non or less structured data? I thought that was the main benefit, or, so to say, that whether you put highly structured data into an RBDMS or a Big Data Apparatus, there wouldn't be that much difference in what you could or couldn't do. However, if you have less structured data to deal with, you would be basically crippled by trying to handle that in an RBDMS, but the advantage of using Big Data for structured data would be negligible.
Once again, both of these are not meant as critical of your article, just want to see if I can confirm my own understanding. Your walkthrough of the Azure Data Lakes product is exceptional, and I know it took you a lot of your own personal time to put that together. You should know that your effort is appreciated. Thanks!