Structuring a big data strategy
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"Big data" has become one of the industry's biggest buzzwords, but another is growing up right along with it: The data scientist. Like big data, data scientist is not a wholly accepted term by the industry, which is still hammering out what it means and if it requires a new set of skills as the title insinuates. But it makes plenty of appearances in job advertisements, vendor pitches and analyst reports.
It also made an appearance at the 11th annual Pacific Northwest BI Summit right in the middle of a presentation. Shawn Rogers, vice president of research in business intelligence (BI) and data warehousing for Enterprise Management Associates (EMA), and Robert Eve, executive vice president of marketing for Composite Software Inc., were giving a talk on data integration and the hybrid data ecosystem.
"We made the terrible mistake of starting out the discussion on how to influence the roles from a data integration standpoint with a data scientist," Rogers said. "And we got off the rail because it's such a hot topic right now."
Definition aside, data scientists are explorers, according to Rogers. They feel their way through all of the data rather than sifting through it for a particular answer. "Data scientists are the guys who walk along the beach with those sweepers looking for that nugget of information that no one knows is in that sea of sand or sea of data," said Rogers.
A better way of defining the term is to figure out where -- and if -- it belongs in the business. While it's been embraced by Web-centric businesses such as LinkedIn and Facebook, not all businesses have the kind of data that would require the skill and technique of a data scientist, Rogers said.
Set against the summit's backdrop in Grants Pass, Ore., Rogers spoke further with SearchBusinessAnalytics.com's news editor Nicole Laskowski about the growing interest in the data scientist.
In this video interview, viewers will learn about:
- How Rogers defines the term data scientist
- What makes a data scientist different from a business user
- Whether the data scientist is a role or a team
- How the rise of the data scientist affects the democratization of data
- How the data scientist trend may affect businesses that can't afford one