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3 Unusual Uses of Big Data

July 4th, 2014 by - 3,378 views

When we think of Big Data, we tend to think big picture – massive amounts of information that is used to accomplish any goal a business or individual may have and that is quickly revolutionizing how we get things done. Although this impression may be true, it doesn’t place enough focus on those who are innovating within the field. Here are three organizations that demonstrate the fascinating range of Big Data technology and its results.

Three companies that are using big data to forward their industries.

Three companies that are using Big Data to advance their industries.

Pricing outdoor marketing
Route, an outdoor media analytics company, has thrown itself fully into Big Data in an attempt to revolutionize and question the standards for pricing advertising using conventional tools like billboards, bench ads, and the sides of transportation vehicles. In previous years, owners of these spaces have charged companies “per impression,” or for every time a viewer sees the advertisement, although there has never been a way to strictly quantify these impressions. Using cloud infrastructure, Route hopes to change that result by gathering live analytics to measure how high the impression rate actually is.

E-consultancy writer Ben Davis described how the company went about the study: “360,000 frames (bits of ad space) are analyzed, both their visibility, with eye tracking studies, and the audience size and demographic that come into contact with the ads,” he explained. “28,000 people were interviewed and then tracked across the U.K. by GPS. Part of this involves traffic studies, too.” This level of precision will allow Route to use Big Data to its advantage to justify pricing.

More accurate, collaborative weather forecasting
Collecting as much information as possible to develop a product has always been the name of the game in weather forecasting, but never before has cloud server hosting technology made it possible to crowd-source this data. An application called WeatherSignal launched in 2013 for Android gives its users the opportunity to collect atmospheric data with sensors that were already installed in their devices, according to an enthusiastic article in Scientific American. Though many of the readings are gathered from phones with varying degrees of sensor capability, the application’s relatively spot-on forecasts are a great example of how the Big Data model operates using mass amounts of “dirty data” as opposed to fewer reads of the atmosphere with more advanced equipment. With users offering their devices as a free forecasting tool, it’s a difficult source of information to resist.

Optimizing personal data and lifestyles
Advocates of Big Data in the office will be happy to learn they can take it home with them by making use of a number of devices aimed at optimizing a person’s daily routine. An excellent example is the UP wristband by Jawbone, which tracks daily activity to help users build a more structured, healthy lifestyle. The wristband collects data while its wearer walks, sleeps, and eats, and then integrates with a complimentary application that synthesizes the information to provide a concise report on the actions taken throughout each day. Bernard Marr, a Big Data analytics specialist, publicized some of the fascinating features of the device in a piece on LinkedIn.

“While it gives individuals rich insights, the real value is in analyzing the collective data,” Marr explained. “In Jawbone’s case, the company now collects 60 years worth of sleep data every night. Analyzing such volumes of data will bring entirely new insights that it can feed back to individual users.”

As these examples demonstrate, Big Data can be tailored to the business it is servicing. That means any company with a specific research goal in mind can take advantage of its highly flexible cloud hosting technology to change something as simple as a price or as complicated as a person’s daily routine.

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The GoGrid Team is committed to bringing you the information, advice, and tools necessary to easily evaluate and deploy a broad range of Big Data technologies and maximize your infrastructure to meet your specific needs.

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