Gartner Magic Quadrant for BI and Analytics Platforms 2017: My Take
After last year's significant changes to the quadrant, it's interesting to see what else has changed since.
You may recall that, in 2016, Gartner narrowed their definition for this quadrant to include only self-service analytical tools. The users of these tools are data-savvy businesspeople – typically the same 20-25% of users who also use Excel extensively – who need to source their own data, manipulate it in any way that they want, and generate insights that (one hopes) they can share with others.
There seem to be additional changes taking place during the shift from 2016 to 2017. Here's a quote from 2017:
Whereas the initial modern BI disruption shifted purchasing from IT to the lines of business — where new tools initially landed as point purchases — as these tools have demonstrated value, enterprise buying of these platforms has grown to the point where the purchasing influence is tipping back to include IT and central purchasing groups. This is further evidence of market mainstreaming and has caused buyers to place greater emphasis on enterprise readiness, governance and price/value, in addition to the agility and ease of use demanded by business users.
Notice that business-driven in 2016 is becoming business-driven with IT support in 2017. Enterprise readiness and governance are becoming just as important as agility and ease-of-use. Point purchases are becoming platform purchases. (That latter is my wording, not theirs.)
Here's another interesting point, one of the six Strategic Planning Assumptions:
By 2020, organizations that offer users access to a curated catalog of internal and external data will realize twice the business value from analytics investments than those that do not.
In other words, self-service data prep is only one platform requirement, and probably for a limited number of people. Most people should use curated data.
(I should note that "curated data" doesn't have to be hard. For years, we've made it very easy to target data sources ranging from spreadsheets to operational systems of record to data warehouses to Hadoop-based data. We used to get criticized for accessing non-warehoused data, but today it's back in vogue. In fact, it's now obvious that all data — on prem, in the cloud, in the public, generated by processes, machinery, anything, is all part of the analytical process.)
In the report, there's a general shift from focusing on self-service tools to "smart" BI — things like natural language generation, search, and other technologies that help patterns in data arise without significant guidance. I agree that these things are becoming more important to make analytics easier.
If I look at the report overall, I think it shows that Gartner is moving to a broader view of what modern BI entails: In Gartner's terms, BI and analytics requires a bimodal delivery model, with both mode 2 (for speed and agility, as represented by things like data discovery tools) and mode 1 (for stability and accuracy, as represented by reproducible analytics derived from curated data). In my opinion, no platform is complete without significant capabilities for both.
It's worth saying that self-service belongs in both mode 1 and mode 2. I think it's important for people to understand that tools address the needs of savvy business users but intuitive apps are required for the broader base of users. It's important to address the needs of both internal and external users — think of non-technical operational users, business partners, and customers — many of whom won't be able to source their own data or use self-service tools. (Look for an upcoming post about InfoApps™ that discusses these ideas.)
Gartner is a prominent analyst group, and it's worth checking out their perspective: You can get the new quadrant here. There are a number of other analyst groups out there with different perspectives, and it's worth checking them out as well: BARC, Dresner Advisory Services, and Ventana Research, to name a few. Read widely to get a full perspective – and tell us your opinion in the comments section.