Recently I attended the Gartner BI Summit in Dallas. If there was any one thing that jumped out at me it was how many of the analytics vendors I spoke with are lowering the barrier to entry for just about anyone to acquire and apply these at their desk, from their hotel rooms, in the airport or on the plane (if they can actually open their laptops in those not-so-accommodating coach seats). It’s a pretty amazing time.
Now we see in Gartner’s annual corner office survey that Business Analytics rank as the top investment priority in the minds of the people who are in a position to know what those investments will be. And a publication as trusted by senior leaders as the Harvard Business Review now sees Data Scientists as the go-to career for the 21st Century. With the stampede to Big Data and all the promise it is heralded to hold we should expect accelerated investment in tools and ascendance of the Data Scientist to elite levels in the organization.
Or maybe not.
There is an ecosystem coming together rapidly that makes me stop and ask myself a few fundamental questions.
- Is the propagation of analytic tools on the desktop and in the cloud going to turn every business professional into a data scientist?
- Is a free-forming analytics marketplace going to form up; sort of an on-demand Analytics App Store with hundreds of thousands of tools?
- Does the potential in Data Science for the masses outweigh its risks?
- And perhaps the biggie: “Is this the catalyst for a new round of explosive growth of shadow IT?”
So I have a fairly simple point of view. Analytics tools in the hands of the business users who ask the business questions is generally a good thing. But it’s a little scary too. With the rush to big data, there are plenty of opportunities to waste plenty of time analyzing things that may not matter, or worse yet reinforce siloes that many have tried to remove. Given easy access to a tool and a vast universe of data, it’s that basic human need to explore that will drive many to capture data that looks interesting, analyze it, apply the insights to their immediate need, and perhaps negatively impact the larger mission of an organization. It’s Shadow IT 2.0.
That creepy, Orwellian word “governance” raises its head here. Something that we seem not to have gotten right in the realm of little data/B.I. is going to be fresh on our minds as we look at BIG data/analytics everywhere.
I’m interested in knowing how sentiment builds along Business/IT/Data Scientist lines. Maybe it’s time for a survey?
We’ll start that process with a simple straw poll in upcoming webinars during our Summer Series. Feel free to join us.