Our economy and unemployment rate seem to be in a constant state of flux.  But one of the most promising jobs in one of the strongest sectors is that of the data scientist, applicable to the tech industry and just about every other market.  But as far as the enterprise goes, where does the data scientist fit in?  In the second episode of our Big Data Deep Dive series, a joint production of EMC TV and theCube, Richard Schlesinger invited SiliconAngle founding CEO John Furrier and Wikibon CTO Dave Vellante to talk about the role of the data scientist in the modern enterprise.

Furrier starts the conversation with a brief explanation of the history of Big Data. He says that it all started out in the database, and gradually moved up (and down) the stack as programmers and practitioners – the people who turn technical advantage into business value – began to work together.

Dave Vellante concurs:

“The alpha geek world and the business world are colliding in a really interesting way. What the alpha geeks are doing is solving the problem: how do I take all this unstructured data and bring structure to it,” Vellante said. He added that “the second dimension we hear from practitioners in the Wikibon community is how do we then create value out of that data? How do we package it? How to we monetize it? How do we distribute it and put it out there?”

Sky is the limit for data scientists

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Vellante says that the sky is the limit, especially now that more and more CEOs are starting to recognize the positive impact Big Data can have on their organizations’ bottom line.  Furrier elaborates on this trend, crediting the increased adoption to one specific innovation: the iPad. Apple’s flagship tablet placed data within the reach of executives for the first time, the same thing the iPhone did for consumers.

The ball bounces back to Vellante, who says that integrating big data into one’s business is easier said than done.

Why?  Because today’s infrastructure is comprised primarily of independent silos, and data analytics will become a silo too, eventually. The only problem is that information is a vital resource in every part of business, which means that IT departments and solution providers will have to figure out how to give all the other silos access to the right data.

This is where Hadoop comes in. Furrier describes the platform as a cost-efficient means to store and rapidly access massive amounts of data: an inconceivable concept in the world of million dollar legacy racks.

Small package, big disruption

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It’s companies like Alpine Data Labs that are enabling the change. Vellante talked to Steven Hillion, the firm’s chief product officer, at EMCWorld 2012 in Las Vegas. Here’s what the executive had to say:

“We sell an application that allows you to do predictive analytics on really large quantities of data without having to setup a massive new infrastructure. In fact what you can do is you can download our product literally off the web, point it at the source of your data –typically it’s gonna be sitting in a relational database like Greenplum for example – and then just start doing predictive analytics.”

“So do you have the capability to essentially, on the fly, build that model in the database?” Vellante asked, a question to Hillion responded with a confirmation: “Yes, that’s exactly what we do.”

The CPO credits Alpine’s ingenuity to a lot of hard work, and major breakthroughs by Big Data pioneers such as Amazon, MySpace and Greenplum.  See the entire segment below, and catch all 6 episodes of this wonderful Big Data series here, on our YouTube channel.