IT and Business Insights for SMB Solution Providers

IoT Data Management: Hot Mess, Scorching Channel Opportunity

Businesses need experts to organize and manage the terabytes of information they’re collecting. By Erik Sherman

THE INTERNET OF THINGS IS A HOT MESS when it comes to data management. Hot because of the many opportunities it presents. Mess because it already generates massive quantities of data and will produce even greater volumes as adoption grows. Indeed, Cisco estimates global data will reach 220 zettabytes—as in 220 billion terabytes—in 2016 and, primarily fueled by IoT, expects that number to hit 850 zettabytes a year by 2021.

Managing all that information is becoming an increasingly demanding challenge. That’s excellent news for channel partners—or at least those that adopt IoT industry best practices.

Brace for the Wave of Data

With big data volumes come big challenges. Hoboken, N.J.-based eMazzanti Technologies, for example, has clients that generate terabytes of data a year. Other companies already generate terabytes of data a day, according to Colleen Balda, a solutions practice consultant at distributor Tech Data Corp., of Clearwater, Fla. Zedi, a Calgary, Alberta-based technology company that monitors oil wells, tops them all, gathering petabytes of data each month, according to CEO Matt Heffernan.

You Know Too Much

That kind of scale has big implications for data management. Balda recommends tackling them with the help of three questions: Which data is important? How quickly does it need to be analyzed? What data structure will be required?

Knowing which data matters will help you reduce the amount of information you manage. “I don’t care about three-quarters of the data,” Leone says. “I have it, and it’s great, but I don’t need it right now.”

Identifying less critical data can be a difficult task, though, as you must ultimately see data in use to know whether it will continue to be worthy of collection. Rick Veague, CTO of IFS North America, a solution provider based in Itasca, Ill., recommends that MSPs start small and build a feedback loop using data analytics and watching what people do with the information. “If you spend too much time engineering what you think the end [goal] is, you could become myopic,” he says.

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