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What will IoT analytics mean for data science?

Analysts like to imagine how IoT data could deepen their statistical models, but most organizations aren't ready for it.

The hype around IoT continues to grow, and some commentators have suggested IoT could be a boon to analytics by serving as a major source of data. But it's unclear whether today's companies are ready to take advantage of IoT analytics' potential.

"The promise of IoT is being able to assemble data from lots of sources, and we're not quite there yet," said David Smith, chief community officer at software vendor Revolution Analytics in Mountain View, Calif.

The slow progress of IoT technology isn't due to a lack of attention. In its 2014 Hype Cycle for Emerging Technologies, Gartner put IoT at the top, which means that the technology has the most inflated expectations. The most notable recent holder of this dubious distinction was big data, a term that many people find at best meaningless and at worst distracting. Gartner previously estimated that IoT adoption will grow to 26 billion internet-enabled devices installed by 2020.

As a data scientist himself, Smith said he is excited about the possibilities that IoT brings in terms of diversifying data sources and enabling analytics to be applied to new areas, such as the monitoring of sensors attached to manufacturing devices.

He also sees growth in IoT analytics creating more jobs for data scientists. In order to make sense out of all that data, companies are going to need skilled analysts.

But there are a couple problems holding back IoT. Smith said consumer adoption of internet-enabled devices isn't progressing as fast as needed. Of course, consumers are snapping up smartphones and personal health monitors, but the commonly cited IoT dream of connected refrigerators -- ones that automatically order more milk when the owner starts running low -- is a long way off.

The second problem is the lack of standards for IoT technology. Smith said all internet-enabled devices produced today come with proprietary software that makes it hard for devices to communicate with each other. He said Google's acquisition of Nest, the learning home thermostat, could help push things toward standardization, as more device manufacturers make their products compatible with Google services. But more progress is needed.

"This is brand-new data and information that we never had access to before," Smith said. "Getting access to data is something data scientists strive for. But all these devices are independent, and there's no way for anybody to aggregate that data together."

Certain industries are likely to embrace IoT much faster than others, said Joe DeCosmo, chief analytics officer at Chicago-based online financial services provider Enova. He previously worked at the consulting firm West Monroe Partners, which manages public utilities clients. DeCosmo said a number were excited about the possibilities presented by smart grid technologies, which involve connecting all points of the power grid to the internet for continuous monitoring, enabling preventive maintenance and proactive management of power supply.

Other industries that control sensor data are likely to embrace IoT. DeCosmo said it would be easiest for manufacturing and supply chain companies to start using IoT analytics since their machines and fleets typically already have internet-enabled sensors or devices. For these industries it's just a matter of collecting the data and applying IoT analytics to it.

Even though some businesses have the opportunity to embrace IoT technology and see some real value from it, few are likely to put in place large-scale IoT projects anytime soon, DeCosmo said. For the time being, at least, IoT remains a dream for the future.

"We're getting to the point where some companies are able to do this at scale, but most are still trying to come to grips with all the data they have now," DeCosmo said. "But it's the future."

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