No longer an arcane topic of conversation among computer scientists and academics, big data is now discussed in executive boardrooms everywhere.
But do CEOs really understand what big data means? And if they don't, where can they go to learn?
In addition to a slew of online sites, books and YouTube videos on the subject, there are a now a handful of executive-level educational programs, offered by universities and commercial entities. More are in the planning stages and should arrive next year.
The programs all share one characteristic: The target student is a business executive.
Yuri Levin, a distinguished professor of management science and operations management at Queens School of Business in Canada, is now in his third year of teaching a two-day big data workshop for non-IT executives.
The class, <"http://business.queensu.ca/executiveeducation/programs/strategic_analytics.php">Strategic Analytics: Creating Competitive Advantage Through Analytics is offered four times a year, and is meant for managers "interested in evidence-based, data-driven decision-making," Levin said in a phone interview.
"Most of these people don't have a technical background," said Levin, who built the class with his Queens School colleague Jeffrey McGill.
"These aren't the people who'll implement [the big data solution], so we're teaching them how to build and organize in general to become more analytical, and what kind of talent is required and where to get that talent." In other words, the goal of Levin's class isn't to teach the executives and managers how to model. "Rather, it's to bring awareness of the techniques," he said. At the same time, Levin is expanding the business school's offerings for technologists, too. In June 2013, it will launch its Master of Management Analytics graduate program. The 10-month program will be taught in QSB's downtown Toronto classroom on evenings and alternate weekends.
Rocco Saverino, CFO at Art Gallery of Ontario, took Levins' big-data class for managers in October. "We struggle with pricing questions, especially around what to charge for [different] membership levels," he said. "Dynamic pricing and revenue optimization are the kinds of things we'd like to explore."
AGO, one of the largest museums in North America, isn't a complete stranger to predictive modeling, and has been using an Excel-based pricing model built a dozen years ago with the help of University of Toronto MBA students. But what Saverino wants to know now is more complicated. "How do you convert a one-time visitor to a member, and move them up through the membership chain to become supporters?" he asked.
He said his ambition is larger than just creating a customer relationship management program, and that now is a good time to rethink how the museum handles data because AGO just announced a reorganization and consolidation of its IT, new media, and Web units.