Ask a dozen CIOs what tops their list of strategic priorities and odds are exceedingly good that "big data" ranks either first or second. One of the greatest challenges, they'll tell you, is finding the talent they need to analyze and wring business value from the ever-increasing volume of complex data flooding their enterprises. What they need, they say, are good data scientists -- and lots of them.
In one of the most frequently cited reports on the topic, the McKinsey Global Institute estimates that there will be a shortfall of 190,000 data scientists in the IT job market by 2018.
But how exactly do you become one of these in-demand big data specialists? Is it a matter of training, certification or both? Is it simply the next logical career step for a traditional business intelligence expert? Is a computer science degree required?
Universities Step Up
The skills required to perform these tasks cut across traditional academic disciplines, including statistics, mathematics and computer science. This is why several schools, including New York University and NC State, offer specialized data scientist certification and degree programs.
"Data used to be something you collected. It had neat rows and columns," explains Rappa. "You ran experiments that were time-consuming, laborious and costly, and you didn't have a lot of data so you dealt with sample sizes."
However, he adds, "data science skills are not necessarily industry-transferrable" because the volume and complexity of data varies from industry to industry. "We're dealing with orders-of-magnitude greater volumes, but the really important part is that the data is much more rich and complex," Williams says.
The optimal place to gain domain expertise is on the job. But for people interested in improving their technical skills, there are options beyond university programs.