Just a couple of months ago, Wired featured a piece where I asked, “Is Big Data in the trough of disillusionment?” It was a very fair question…there has been so much positive said about Big Data that it would be hard (or impossible) to maintain the expectations being set.
To get Gartner’s July 31st update’s full take, you’ll need to download the report, which is exhaustive and breaks down the many components of what make up the hype, from new ideas, like quantified self (how we create data about ourselves that is useful to us and to others with Jawbone UP, Nike, FitBit Tracker, etc.)to ideas that are still years away, like telematics.
Still at the peak of big data’s hype
Gartner believes that we’re still at the peak when it comes to Big Data, but recognizes like many of us that the term is being overused by plenty of people who’d like to take advantage of the hype. That doesn’t by any stretch mean Big Data is dead or dying. Quite the opposite…it has become so established that the market is starting to see the application saturation that will replace the clunky nature of the original open source software like Hadoop and Hive.
Arrival of applications
And the applications are here. In a piece for Harvard Business Review, I showed how applications that perform machine learning, a concept that has been around since computerization, are now becoming a key part of how Big Data is used for healthcare and other fields. This arrival of tangible, value-driven applications is one of Gartner’s measures for when a technology reaches the Plateau of Productivity.
Likewise, Gartner points out (and the market bears out) that predictive analytics are well into the Plateau, led again by applications. In this case, those applications are being used by business users, the true experts, to visualize data very quickly to make predictions rather than simply understanding what’s already happened. This week, we’ll focus on visualization and predictive analytics.
Where Big Data stands
The Gartner report points out what should be intuitive to anyone working in Big Data…that this concept is so large and encompases so many aspects of business and personal life that it can’t be captured simply as a dot on a hype cycle. Each aspect of Big Data is at its own place on the cycle and the piece that matters most is whatever a particular use case requires. That’s the best reason that when someone asks me what I think of Big Data, my first question back is, “What do you mean by Big Data?” Frankly, it means something different to everyone.
I’ll be managing the Big Data Workshop at Interop New York on October 1st. I hope to see you there and together we’ll tackle Big Data’s nuances, hype and reality.
Good reading on Big Data
In the meantime, some good reading on Gartner’s Hype Cycle for Big Data:
Radar O’Reilly - Big Data is Dead, Long Live Big Data
Gartner Research Director Svetlana Sicular - Big Data is Falling into the Trough of Disillusionment
ZDNet - Bigging up big data – Why the hype is about to stop
GigaOM - If you’re disappointed with big data, you’re not paying attention