IBM’s Scott Oliver talks Big Data analytics with Medill IMC students
With more people in possession of cell phones than working toilets, there is clearly a massive amount of data—more than we know how to use—generated every day. Scott Oliver, SEO specialist at IBM, broke down the magnitude and opportunity of this data in a virtual presentation to Lecturer Randy Hlavac’s IMC 482 Digital, Social, Mobile Marketing class. Oliver stresses the importance of “building a culture that infuses analytics everywhere, and empowers all employees to make analytical decisions.”
Before beginning the presentation, Oliver called for a show of hands of who felt comfortable with their understanding of big data analytics. After a moment, two people hesitantly raised their hands and Hlavac relayed the count to Oliver, who replied “now that’s a good representation of the entire population."
He explained the focal points of big data through the four V’s: volume, variety, velocity and veracity. Big data, according to Oliver, is a huge volume of data—it accounts for about 2.5 billion laptops full of information every day, with data housed on everything from social media accounts to Laundromat machines.
“The velocity of big data is very close to real time, thanks to advances like stream computing which gives analytics in approximately 30 seconds,” Oliver said. ”Because of its novelty, there is still distrust in the veracity of big data, which I work to overcome with rigorous methodology [as a data analyst].”
The biggest challenge is linking all this data together, something taken on by IBM in their new unit Watson Foundations. Hlavac said students in IMC can expect to gain experience with similar cutting edge technology thanks to the OmniChannel Initiative, which is supplied by IBM with state-of-the-art database, real-time warehousing, social monitoring, real-time marketing, mobile and other software. In this initiative, students and faculty collaborate to address real-time digital communications problems from an “omnichannel” perspective—combining big data analytics and insight-driven marketing across social, mobile, web, retail and traditional media. This program is very promising for students looking to go into this kind of analysis, but in terms of gaining experience, “even excel has gotten very sophisticated,” Oliver stated.
As a conclusion, Oliver showed the application of big data analytics in an IBM client case of a mobile carrier company. Big data analytics were used to achieve effective customer management by combining enterprise content, location and social data to predict and gain insight into consumers’ phone habits, enabling the company to come up with a plan to save the customer money.
This is just one example of the uses of big data—Oliver also cited cases of using analytics to explain how Facebook finds acquaintances as potential friends, and how retailers personalize coupon distribution. Anyone looking for a fertile industry should consider big data analytics, Oliver recommends; there are “jobs for 4.4 million data scientists and only 1.5 million to fill them right now…there are a handful of universities in the U.S. with this specialty and NU is one of them” he reports.
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