Jawbone is the San Francisco company behind the Up band, which many consider as the early leader in the fitness- and activity-tracking market.

So we’re particularly excited to announce that Monica Rogati, Jawbone’s vice president of data, will be speaking at our DataBeat/Data Science Summit event on Dec. 4 and Dec. 5.

Rogati joins an all-star roster of the best thought leaders in data science today. We’ll psyched about this event, because it is one of the first times anyone has brought together data scientists and business executives in the same room. And there are few areas more interesting for the use of big data than in how it can help us track our own activity and make us better — at whatever it is we’re trying to do, whether that’s sleep better, run faster, or stay nimble by signaling us to get up and move around more often.

We’ll be announcing more rock-star speakers for DataBeat over the next few days.

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Jawbone’s significant share of a growing market gives it quite a lot of data to mine. According to Rogati, the company collects the equivalent of 60 years of sleep data every night.

Sleep, of course, is only a part of what the band monitors. For Rogati, Jawbone’s data trove was too good an opportunity to pass up. She joined the company this past summer from LinkedIn, another data-driven powerhouse. At Jawbone, she’s building a team to mine the data for insights that could help motivate Up wearers to live healthier lives.

Today, most of the value wearers get from bands like the Up (and its competitors) is personal. You simply see your own activity, plus progress toward any goals you may have set around activities such as number of steps taken in a day.

One notable move by Jawbone is its embrace of third-party developers. Rogati’s company is hard at work, aggregating (and anonymizing, of course) all those individual step counts and sleep logs and activity measurements — and then combining it with data from third-party applications such as Foursquare. The resulting data offers a compelling glimpse into millions of lifestyles. Patterns quickly begin to emerge, illustrating trends which might vary by age, sex, or location.

Mix all that in with your smartphone’s GPS and you can do even more. If someone consistently checks in at Pizza Hut just before a restless night, maybe the app linked to their Up could nudge them to skip the late-night pizza feast.

Indeed, the first task is to turn patterns into data-driven stories that can be shared with the world. The second — and harder — one is to put the data to work in ways which can begin to inform and change an individual’s behavior.

Jawbone is a company facing a very familiar transition, as it shifts from a focus on hardware design and engineering (fitness tracking wrist bands, portable speakers, Bluetooth headsets, and the rest) to building a business powered by data. Rogati, a founding member of the data science team at LinkedIn, has the task of finding the right people to help Jawbone successfully make this transition, and she’s not filling her team only with mathematicians. Instead, particle physicists, neuroscientists, and astronomers are on her list. These are people used to dealing with large volumes of noisy, messy data.

Jawbone’s strategy will likely play out over several years. It is just one leader among companies across all industries that are embarking on a journey to give a central role to the information that their customer generate.

Jawbone gets its data through a clever exchange. First, it offers an easy-to-use way to monitor your activity, in exchange for the access to your data. It has since gathered such massive amounts of data that it can uncover patterns that would be missed by experiments of smaller scales. The company feeds personalized advice back to each of its customers, increasing the value of its basic service, but also enabling it to tailor its updates to products and services to a user base it knows more intimately than ever.

The approach of replacing guesswork and habits by verified insights is taking hold well beyond fitness. It’s spreading to traffic rules on busy roads, grading high school students, and measuring the effects of weather on crops yields or heavy machinery. The companies doing it best will be the ones that gather the best data aggregated for the longest time, a undeniable competitive advantage. A Bluetooth headset manufacturer has grown into the major contender in the fitness-data sector within only a few years. It is still early to tell which companies will best blend usability, reach and data processing capabilities to conquer the data pipe in other markets. One thing is sure, most got started already.

You’ll hear this, and other amazing big data stories, at DataBeat in December. See you there!

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