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How many data scientists does the world really need?

Sharon Florentine | Nov. 8, 2013
The buzz is all about 'Big Data' and how best to use it to generate actionable intelligence. To do this, companies will need to hire loads of highly trained, highly paid data scientists -- or will they?

Most large enterprises, looking for a competitive edge, will jump at the chance to hire folks who can use the data they've collected to try predicting the future of the markets, sales cycles and trends, and customer behavior rather than just react to what's happened, Gaskell says.

"If you want some predictive analytics, you're going to need to hire a few of these data scientists, but whole armies? That'll be too expensive," Gaskell says. Instead, enterprises will find ways to train business and financial analysts, as well as the 'average business user' to perform data analytics using automated tools.

"The feedback we're getting from customers is that they want just a handful -- maybe three, or five, or seven -- skilled and highly educated data scientists," says Michael Hiskey, Kognitio's vice president of business development and marketing.

Then, enterprises will surround those with business analysts, then surround those folks with a group of interns," Hiskey says. Kognitio itself has seen great success with such a hierarchy that it calls the Kognitio Analytics Center of Excellence (KACE), he says.

Big Data Reality vs. the Hype
For now, it seems, the rush to mint highly trained, highly educated data scientists can be chalked up hype and buzz, especially since the IT industry is still in beginning stages of big data usage and relevance, according to Ankur Gupta, head of global sales and marketing at MetaScale, a Hadoop solutions provider.

"Sure, enterprises are looking for folks with a statistical and predictive modeling background that can dig deep into data, understand trends and how to spot them, but they also have to have the patience to wait until trends and activity become clear," Gupta says.

"Right now, we see a trend toward companies wanting and needing that human touch, the expertise to parse data and use it to make decisions. But we're in the early stage of big data development, and as technology catches up, we believe that companies will offload these functions to machines, software, to technology. You don't need to hire ten data scientists to do the job," Gupta says.

 

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