Please, do you mind sharing what exactly makes a BI solution difficult/struggling for 1,000+ users?
Is it something technically related or more business/feature related?
Is it something technically related or more business/feature related?
Tech-wise, data stacks are complicated. Hundreds of pre-existing tools, with many owners and diverse interests. BI is where they all meet. With some organizations its easy to build a central data warehouse, but in a large corporate environment that's a dream. Imagine how many data warehouses an organization like Microsoft might have? OK, MS is too large - how about Expedia or Zillow? Thousands? So you connect a tool like Looker--that was designed for 2-10 connections--to a thousand? How do you even administer all the connections? How do you govern access? Access permissions at Looker (and other BI tools) are great, but it would take you 10 years to set them up for 1,000 DBs. And what about tool access? Some want SSH tunneling, others want complete on-prem. Some need Google authentication, while others want one through a pre-existing corporate login. Most large organizations typically end up building--or hiring someone to build--their own custom solutions on top of these tools. Such custom solutions are bigger projects than the implementation of a BI tool to begin with. Oh, and most also fail. The success of a BI in an enterprise environment is partly good sales/marketing/support, but a big part is due to the product achieving some form of maturity with all this side tech--the stuff totally not core to the analytics itself.
Business-wise, try getting people with diverse backgrounds agree on common terminology. Let's take marketing for instance. Should be easy, no? But hey, marketing is actually like 10-20 different kinds of people - some know SQL, others can't put 2+2 together and arrive at anything other than the word "magic". Some think in terms of stories--others think in terms of conversion funnels. OK, so you've put together some data dictionary, did some training, segmented users into 1) technical ones (SQL/LookML/BackML...), 2) business (explore), 3) consumers (dashboards/pretty charts). But now it turns out that much of the data they rely on is generated by a different team--say, operations or sales. Again, you've got 10-20 different kinds of personalities there. Somehow all these people have to agree. How do you make them all agree? Short answer: you cannot. No one can. They don't even like speaking to one another - and now you are going to come in and make them agree on what kind of KPI is going to determine their success => bonus. Hell no!
There are ways to make progress on both fronts. And, no doubt, an open source project has some chance. But it is not easy. And no one has really done it in 30 years. Many have tried.
Full disclosure: I love BigQuery (Google Cloud partner). Love Looker. Rely on Open Source constantly. Just trying to demonstrate a realistic view of how hard this problem is.
Again, if you don't mind sharing, what would be a dream solution for you, something that could solve most of the problems you mentioned?
I understand that some of them are cultural problems (like people no talking to each other), but maybe somehow a technology could solve this?
If you could think of a new approach, what would that be?