How To Build An Analytics A-TeamHow To Build An Analytics A-Team
Five key big data roles will emerge as analytics tools become more popular in the enterprise, says one analyst firm.
November 11, 2013
5 Big Wishes For Big Data Deployments
5 Big Wishes For Big Data Deployments(click image for larger view and for slideshow)
We often hear about the shortage of data scientists, but less about the need for big data support personnel: business intelligence workers who take data-generated insights and use them to make an organization more effective. What roles will these support positions play, and who's best qualified to fill them?
According to Blue Hill Research, a Boston-based research firm, five job functions will emerge as more enterprises adopt big data analytics tools. As outlined in a recent blog post on the company's site, these five roles include: data evangelist; contextual analyst; data visualizer; data custodian; and neuro-analyst. [ Can you shift some of your current workers to fill your big data needs? Read Can Your SysAdmin Be Your Data Scientist? ] "We think of this as kind of the Analytics A-Team," said Blue Hill Research principal analyst David Houlihan in a phone interview with InformationWeek. So what are these jobs exactly? Here's a quick overview: 1) Data evangelist: This new position won't require formal data science training, but rather an expertise in a specific business area, as well as a curious nature and a knack for finding new business uses for big data. "The job is less about crunching the data … and more about identifying use cases for data," said Houlihan. For instance, the Blue Hill Research blog points to the increased usage of baseball statistics over the past decade, as stats-minded enthusiasts crunch data in new ways to show how on-base percentage matters more than battling average. "These changes have been driven in large part due to fans' concerted baseball specific analyses of data that had already existed for years prior," the blog states. 2) Contextual analyst: Here's a promising career path that could provide gainfully employment for English PhDs rather than programmers. The contextual analyst's role is to understand the meaning of data, particularly as its relevance and importance evolves, something today's algorithmic models aren't very good at. "It's very easy to look at the data, look at your results, and think you know what's going on," said Houlihan. "But you need that extra layer of contextual understanding to drive really effective insights." In essence, this job highlights the "touchy-feely side" of big data. Said Houlihan: "It's the ability to wrap the quantitative back into the qualitative, so that you really get the understanding and context around the data." 3) Data visualizer: Here's the flip side of the contextual analyst, a position that requires skilled artists, game designers, and other visually-oriented folks capable of turning big data into innovative "instinctual graphics" that go beyond conventional bar charts and line graphs. "This isn't about the context as much as it's about presentation," said Houlihan. "Graphic designers have all kinds roles that they can play within an organization." 4) Data custodian: A core technical support role, the custodian is the caretaker of the organization's data. In addition to being trained in metadata and data structure management, this individual must also be good at aligning data sources with an organization's goals. "There's a lot that can be automated around data cleansing, but there are still things that can't be neatly reduced to heuristics," said Houlihan. "There's a judgment call involved that's based on experience and understanding of data." 5) Neuro-analyst: A skilled neurobiologist who understands how cognition works, and how an organization can develop strategies to present data in ways that people can easily grasp. The neuro-analyst probably isn't a position that organizations will be filling immediately, Houlihan said, but rather one that will gain importance as big data initiatives grow and mature. For more specifics on the five new roles for business intelligence, check out the Blue Hill Research blog. Emerging software tools now make analytics feasible -- and cost-effective -- for most companies. Also in the Brave The Big Data Wave issue of InformationWeek: Have doubts about NoSQL consistency? Meet Kyle Kingsbury's Call Me Maybe project. (Free registration required.)
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