IIA sees data science as resting on three legs: technological (IT, systems, hardware and software), quantitative (statistics, math, modeling, algorithms) and business (domain knowledge), according to Phillips. "The professionals we see that are successful come from the quantitative side," he says. "They know enough about the technology but they aren't running the technology. They rely on IT to give them the tools."
Big data also demands a scientific temperament, according to Wills. "When we talk about data science, it's really an experiment-driven process," he explains. "You're usually trying lots of different things, and you have to be OK with failure in a pretty big way." Wills speaks of a "certain kind of relentlessness you need in the personality of someone who does this kind of work."
When we talk about data science, it's really an experiment-driven process. You have to be OK with failure in a pretty big way. Josh Wills, Cloudera
They also have to be intellectually flexible enough to quickly change their assumptions and approach to a problem, says Brian Hopkins, a principal analyst at Forrester Research. "You can't limit yourself to one schema but [need to be comfortable] operating in an environment with multiple schemas or even no schemas."
That tends to be a different operating model than most IT people are used to, he says. "IT people coming out of a strong enterprise IT shop are going to perhaps be constrained a little bit in their ability to do things quickly and move fast and be agile," Hopkins says.
But hiring managers, once they find the right type of person, are usually willing to retrain that person to fill a big data role. At LinkedIn, says Patil, "we largely trained ourselves, because so much of this is open source," and he thinks most companies can do the same. "You can make these people" -- if they have the right personality, he says.
As for employees, certain IT folks would love to flex a more creative muscle in their jobs, and they may be able to segue into a big data career. If an IT worker is flexible, willing to learn new tools and has a bit of the artist in him, he can move into data architecture or even data visualization, says Sacheti.
For the certain subset of IT workers who "would relish the opportunity to show their creativity," big data carries big potential.
Frequent Computerworld contributor Tam Harbert is a Washington, D.C.-based writer specializing in technology, business and public policy.
Read more about big data in Computerworld's Big Data Topic Center.