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Hype is rising over sensor data but success will hinge on fundamentals

The buzz is on for sensor data but extracting value, as always, will hinge on mastering the data fundamentals: The Data Mill reports.

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The enthusiasm for the Internet of Things (IoT) is like big data déjà vu. That's how it felt to this big data reporter at the Massachusetts Technology Leadership Council's recent Value of Things conference. Cisco Systems Inc. and Verizon Communications and Oracle Corp. paraded out anecdotes of how sensor data will ensure easier urban parking, less invasive medical procedures and even decent wine.

"Folks in Napa are starting to instrument their vineyards," said Jim Grubb, vice president of emerging technologies and chief demonstration officer at Cisco. And they're not just slapping a sensor here and there, "they're instrumenting every single vine in their vineyards." That's saving vintners 30% on their water bills, according to Grubb, because "they're only watering those grapes exactly the right amount."

There were other, even more compelling examples, like equipping "ingestibles" or "smart pills" with the ability to take photographs or to monitor heart rhythm from inside the patient's body or blending data from disparate sources to uncover why a certain area might trigger asthma attacks.

The Data Mill

Still, similar to the initial buzz around big data, IoT discussions evoke excitement about the wonderful possibilities: New business models! Competitive advantage! Deeper insights! And they often leave out what's practical, as Poul Peterson, chief infrastructure officer for Corvallis, Oregon-based BigML Inc., noted during a panel discussion on data analytics. Attaching sensors to every grape vine, cargo ship, train car or transformer, "that's not too hard," he said. But "how on earth do you get to that last step?"

By last step, Peterson means how do you mine sensor data to find what he called those "aha moments," or correlations between two seemingly unrelated data points. Sensor data is "big in terms of complexity," giving businesses millions of data points to dig through. "You don't know at the outset if two things are related," he said. "Or you may just get it wrong." It should be noted BigML is in the business of helping companies make the leap into advanced analytics to find those correlations, but still, Peterson's perspective was more than an on-message advertisement. As CIOs know from forays into other types of big data, rich insights don't just fall out of the data -- not even for a data scientist.

Take it from Nicholas Arcolano, senior data scientist at Boston-based RunKeeper and MassTLC panelist. He tells those who hire him that "almost half of what I'm going to tell you is not going to surprise you at all." The other 50% of the data he typically dishes up are "bugs in the data" with a dollop of aha. "There's going to be a little sliver in between where I find something remarkable and unexpected," he said.

Instrumenting the world is generating tremendous excitement and cloud, open source technology and programming languages such as Python are making data science and data integration "easier than I could have imagined 10 years ago," Arcolano said. Still, some things don't change. For CIOs, IoT means keeping an eye on IT essentials: Data cleansing, data governance and master data management are still a priority if businesses are going to find those remarkable slivers.

The Internet of (every) Thing

Cisco's Grubb believes the term IoT is too narrow. He's partial to the term Internet of Everything. Coined by Gartner analyst Hung LeHong, the Internet of Everything includes networks of people and networks of locations, Grubb explained.

"Oftentimes we want to take that insight that comes to us in the data," he said. "And then we want the ability to do something in context. And, often, that context is location."

Take the Voyager Legend, the Bluetooth headset from Plantronics Inc. in Santa Cruz, California. It has a built-in compass, gyroscope and accelerometer, which means the phone's GPS can reveal where you're standing and the headset knows what direction you're looking in, Grubb said. New business applications, including those for the retail and gaming industries, could be built around that kind technology, he said.

"People are not just consumers," he said. "Sometimes they are the sensors."

The innovation game

The Verizon Innovation Program, with locations in Waltham, Massachusetts and San Francisco, searches for partners who have innovative ideas but may not have the means to get the product to market, according to Mary Beth Hall, director of marketing for Verizon's connected solutions department.

Hall mentioned two successful projects at the MassTLC event: VGo, a virtual student used in classrooms, and the Golden-I mobile computing program, which helps firefighters locate survivors, navigate floor plans with greater ease and "monitor firefighters' heart rate and oxygen levels" according to the website.

And Verizon's not the only company tapping into creative thinking or finding products to bring to market. Earlier this month, Microsoft launched a new startup accelerator in partnership with American Family Insurance. The accelerator will focus on the home automation market.

Say what?!?

"Before, [data] was all very proprietary, very siloed. So, from that perspective, what we have now is a lot data that's not actually new. What is new is the blending you can do of that data with other more relational and structured kinds of data." -- Javed Jahangir, director of big data technology, Oracle

"High volume doesn't necessarily mean high value." -- Christopher Rezendes, president, INEX Advisors

"We've only connected 1% of the physical things that will be connected to the Internet." -- Jim Grubb, vice president, emerging technologies and chief demonstration officer, product and solutions marketing, Cisco Systems

"IoT is beautiful concept, but the challenge is, it is a concept. Progress is built on architecture." -- Sanjay Sarma, director of digital learning at MIT, founder of MIT's Auto-ID Center

Last week on The Data Mill, Intel solves a big data infrastructure problem with APIs.

Welcome to The Data Mill, a weekly column devoted to all things data. Heard something newsy (or gossipy)? Email me or find me on Twitter at @TT_Nicole.

This was first published in June 2014

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