September 20, 2012, 11:30 AM — As big data gathers momentum, there's a big career opportunity building as well -- for professionals with the right qualifications, that is.
According to a report published last year by McKinsey & Co., the United States could face a shortage by 2018 of 140,000 to 190,000 people with "deep analytical talent" and of 1.5 million people capable of analyzing data in ways that enable business decisions.
Companies are, and will continue to be, looking for employees with a complex set of skills to tap big data's promise of competitive advantage, market watchers say. "There's no question that the number one requirement [for] enterprises that are serious about gaining a competitive advantage using data and analytics is going to be the talent to run that program," says Jack Phillips, CEO of the International Institute for Analytics (IIA), a research firm.
But what exactly constitutes "big data talent"? What are these jobs, and what skills do they require? What kind of background qualifies a person for a big data job? Computerworld took the pulse of some prominent players in the emerging field to determine an IT worker's place -- if any -- in the big data universe. Here's our take.
Buckets of skills
"There is no monolithic 'big data profession,'" says Sandeep Sacheti, former head of business risk and analytics at UBS Wealth Management. He was recently hired for a newly created position, vice president of customer insights and operational excellence, at Wolters Kluwer Corporate Legal Services.
Sacheti's new job is all about big data: using analytics to understand customers, develop new products and cut operational costs. In one project, the Wolters division that sells electronic billing services to law firms is using analytics to mine data it's gathered from its customers (with their permission) to create new products, including the Real Rate Report, which benchmarks law firm rates around the country.
Some big data job tiles contain neither the word "big" nor the word "data."
Sacheti is now both hiring from the outside and training internal staff for big data work. He thinks of big data jobs in terms of four "buckets of skillsets": Data scientist, data architect, data visualizer and data change agent (see Big data skills and titles for details).