IoT Data Management: Hot Mess, Scorching Channel Opportunity
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.
Don’t Forget the Processing
Moving massive flows of IoT data across the network can be difficult. “As you start to see hundreds of sensors, thousands of sensors, tens of thousands of sensors on the network [it] can slow down traffic,” says Adam Petrovsky, GovEd practice leader of Logicalis, a global IT solutions provider headquartered in New York.
Edge processing can ease the challenge, he continues, pointing to the company’s work on the digital transformation of the Ohio Turnpike as an example. Using locally installed processing power speeds up system performance by decreasing the amount of information the system must exchange across the cloud. “The data is being analyzed on the device,” Petrovsky says. “It dramatically changes how you manage data at scale.” Edge processing also helps reduce network latency, he adds, and accelerates data analysis.
Managing the Platform
Figuring out where to store IoT data is an important consideration too. Zedi, which often houses data in the cloud, equipped its custom-developed sensor platform with APIs that support all three of the leading infrastructure-as-a-service environments.
In-house data warehouses are another possibility, albeit a potentially expensive one. A third option, according to eMazzanti Technologies CEO Carl Mazzanti, is to subsidize storage costs by selling the data to companies that repackage and market information from third-party suppliers, like Dawex Systems or the Climate Corp., which buys IoT data from large manufacturers of agricultural equipment. Such firms typically give data originators ongoing access to their information, enabling them to offload storage infrastructure while still retaining use of historical information.
Regardless of where you store IoT data, however, be sure you can repurpose your data management solutions for other customers. Even off-the-shelf hardware and software systems can usually be tailored to meet a variety of vertical market and business-specific applications. That will save you time and money and lower the employee learning curve as your IoT practice expands.
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