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August 20, 2014

Most Hyped Tech: Big Data Out, IoT In

Alex Woodie

The Internet of Things (IoT) has displaced big data as the most hyped emerging technology according to the latest release of Gartner’s Hype Cycle. Big data’s drop into the “Trough of Disillusionment” and the IoT’s rise to the “Peak of Inflated Expectations” indicate continued evolution of these related concepts, but are reminders that these are early days for both, and the claims of salesmen may not match reality.

For the past two years, the hype surrounding big data has been thick enough to cut with a knife. Much of this hoopla surrounded Hadoop, NoSQL, and in-memory database vendors and the novel ways they enable organizations to store, process, and analyze vast amounts of data. Venture firms have poured billions of dollars into the big data space, but few Hadoop or NoSQL companies have turned a profit yet. Making money can come later—today the race is all about achieving scale and dominance in markets that are expected to balloon in value over the next few years.

The practice of peering into a crystal ball is as much art and science, and you should be careful not to read too much into it, or let it dissuade you from reaching your goals. Just the same, it’s useful to take a step back from one’s own work and take a look at the broader macro-level view from time to time. Gartner‘s predictions are tremendously influential in the IT world, of course, and can help make or break a given sector of the technology industry. The venture capital spigot can turn off just as quickly as it turned on, and the views of elite analysts like Gartner’s can play a role.

As you can see from the graphics below, from 2012 to 2013, big data scaled the “Peak of Inflated Expectations” in Gartner’s Hype Cycle, and in 2014 it went over the edge into the trough. Big data has a few more years before it completely bottoms out in the trough and begins the slow climb up the “Slope of Enlightenment” and ultimately the “Plateau of Productivity.” In other words, we’re a long way from ordinary organizations being able to take advantage of big data technologies without making big investments. We’re still in the era of first-mover advantages.

trough of disillusionment_2014

Gartner’s 2014 Hype Cycle for Emerging Technology

Gartner's 2013 Hype Cycle for Emerging Technology

Gartner’s 2013 Hype Cycle for Emerging Technology

The rate of big data’s maturation is a bit iffy. It may be tough to tell from these graphics, but in 2012 Gartner predicted that big data would reach the plateau in two to five years. Apparently, big data regressed a bit and in the 2013 report, Gartner said big data was five to 10 years away from the plateau. It had the same timeframe in the 2014

Gartner's 2012 Hype Cycle for Emerging Technology

Gartner’s 2012 Hype Cycle for Emerging Technology

report. Apparently, either the hype level has increased or the technology has not progressed as fast as initially expected, or there’s some combination of both.

Meanwhile, the Internet of Things has displaced big data as the hot young thing in IT. As a catch-all for any machine-generated data that travels across the Net, the IoT is a superset of big data that holds an equal amount of promise in industrial applications (think real-time turbine optimization or predictive maintenance on fleets of trucks) as it does in consumer technology (think a fridge uploading milk levels and Fitbits collecting vitals).

The IoT has progressed quickly, and is expected to reach the plateau of productivity within the five to 10 years timespan, up from a 10-plus year timeframe in the 2013 and 2014 Hype Cycle reports. But, as we can infer from the IoT’s positioning, you can expect some IoT letdowns in the coming years, as the technology matures and the kinks are worked out. First-mover advantages are to be had right now in the IoT; check out our recent story on GE Intelligent Platforms to see how.

Meanwhile, several other related technologies have matured a bit in Gartner’s eyes. Cloud computing has inched its way down the trough and is within striking distance of beginning its climb up the slope towards higher ground. The hype surrounding in-memory analytics bottomed out in 2012 and now that tech segment is within two years of hitting the plateau.

However, in-memory database management systems (for transactional systems) have been stuck for the past three years in a very lonely place that’s on the backside of the Peak of Inflated Expectations and the edge of the abyss of the Trough of Disillusionment. Gartner remains upbeat, however, and see the in-memory DBMSs pulling out within two to five years (a timeframe it’s maintained for the past three years).

Spending on big data continues its big rise. In a report earlier this year, IDG said the average organization will spend about $8 million on big data projects this year as they try to get a handle on data that’s expected to nearly double over 18 months. Gartner itself said that firms will spend a total of $44 billion on big data projects this year, much of it spent on services.

While these numbers sound impressive, the truth may sit slightly below the surface. IDG found that enterprises are spending considerably more than smaller companies, so using the “average” skews the results. In a report last year, Gartner found that fewer than one in 10 companies around the world had active big data projects, such a Hadoop or NoSQL implementation; other groups have found similar numbers.

The promise of big data analytics is definitely great, but the hype is almost unbearable at times. As your big data journey unfolds, keep a skeptical eye for claims that sound too good to be true. We’ve got a long way to go before the technology can match the hype. If you can handle the bumps of rolling your own big data solutions, you can get advantages from big data technology now. But if you’re expecting a smooth roll-out, it’s best to wait.

Related Items:

How GE Drives Big Machine Optimization in the IoT

The Big Data Market By the Numbers

Big Data: Beneficial or Bunk?

 

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