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Structuring Big Data With Information from Mobile Devices

By CIOinsight  |  Posted 03-24-2011 Print
Adding information from mobile devices and geolocations provide valuable insights to improve predictions using massive data sets.

Making use of space-time-travel information in analyzing big data can give organizations an improved understanding of trends and customer behavior. Organizations are already taking information they've collected and analyzing it to gain improved insights into customer behavior, but the ultimate opportunity lies in analyzing geolocational data to figure out where people will be at a given time, said Jeff Jonas, an IBM distinguished engineer and chief scientist at IBM Entity Analytics.

Jonas presented the morning keynote for GigaOM's Structure Big Data conference in New York City on March 23. While using "space-time-travel" would be an enormous opportunity, it will unravel secrets and challenge existing notions of privacy, he said. Big data refers to data sets that are too large and awkward to collect, store and analyze using traditional database management tools.

Despite privacy concerns, Jonas was enthusiastic about big data, noting that having large data sets means companies are able to improve the accuracy of their predictions. Incidents of false negatives and false positives are also reduced, he said. The computing time required to obtain the data also decreases, meaning the enterprise has quick access to an increased amount of data, he said.

Anyone who carries around a smartphone or any mobile device with GPS enabled is constantly broadcasting where they are, Jonas said. Cell phones are generating a "staggering amount" of geolocational data, more than 600 billion transactions per day in the United States alone, Jonas said.

The data quickly reveals where people spend most of their time and who they spend it with, he said. "Deidentified" does not mean "true anonymization," especially in large data sets, Jonas said. Figuring out who is who is "somewhat trivial," he said.

It is possible to predict with "87 percent certainty" where someone will be at a certain time in the future, he said. A government intelligence service could pre-empt the next mass protest in real time based on geolocation data alone, he said.

For more, read the eWeek article Big Data Keynote Focuses on Analyzing Geolocational Data for Insights.



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