By Howard Baldwin
Nov. 24, 2014 11:06 a.m.
It’s become clear in the past few years that few technologies live in a vacuum. They’re more likely to be connected or related and sharing data, which is why it’s always better to think of the enterprise holistically rather than in silos. (Imagine how much more efficiently the federal government would run if it stored one record of each citizen, rather than one at the Internal Revenue Service, another at the Social Security Administration, another at the Transportation Security Administration, and so on.)
That’s also why you’re hearing the term SMAC bandied about more recently. That’s the amalgam of social, mobile, analytics, and cloud, because the four work better together than individually.
Similarly, the close sibling of analytics, big data, also feeds off the Internet of Things. Admittedly, I think we’re much further along with big data than we are with the Internet of Things, especially since, as Forbes contributor Gil Press noted wryly earlier this year, the Internet of Things has surpassed big data on the Gartner hype curve.
But once the Internet of Things gets rolling, stand back. We’re going to have data spewing at us from all directions – from appliances, from machinery, from train tracks, from shipping containers, from power stations. I loved the infographic on the Big Data Startup site about all the ways we’ll come to collect sensor data. If that doesn’t get you thinking about how to handle real-time data feeds, nothing will. But here’s a suggestion: start now.
You may still have time. GigaOm’s Derrick Harris noted last week that the Internet of Things isn’t producing a data deluge … yet. But the analytics challenge is nonetheless looming. As Harris rightfully says, after citing Cisco’s prediction of 21 billion connected devices by 2018, “the companies that will be storing all that device data are less concerned [about] sheer volume and more concerned about making it usable.”
Some companies are already starting. As Drew Robb noted in his Enterprise Apps Today article last week, How IoT Will Change Big Data Analytics, Duke Energy’s Emerging Technology office is thinking about how to take advantage of communication from buildings, vehicles, people, power plants, and smart meters.
As one of Robb’s sources noted, “Every enterprise needs to factor in how the Internet of Things is going to affect them and their business, and must respond by establishing the right infrastructure to support this level of Big Data and analytics. If they don’t, they will fall behind.”
On the other hand, there are others who aren’t responding with any urgency. According to Jeff Bertolucci’s news report in Information Week last week, the Computing Technology Industry Association (CompTIA) released a survey showing that while a shade over half of respondents believe “Internet of Things opportunities justify the hoopla,” an almost exact percentage, 48%, “see more hype than substance.”
Bertolucci suggests, quite accurately, that IT executives may be hesitating because of a lack of standards and the potential inability of sensors to share data. But as a CompTIA executive notes – also accurately – that this little thing called the Internet “required certain protocols to become commonly used” before we started deriving full benefit from it.
But no matter when you start – today, tomorrow, this weekend, not later – remember this sound advice from a Booz Allen consultant, quoted by ZDNet’s Larry Dignan last week. “Machines do analytics; humans do analysis.” Dignan added, “Computers are good at detail and examining the past, but real data science requires imagination and cognitive ability.”
The moral of the story: you can have all the sensors in the world, but you’re still going to need someone to figure out what they’re telling you.
Original article at: http://www.forbes.com/sites/howardbaldwin/2014/11/24/a-match-made-somewhere-big-data-and-the-internet-of-things/