How to get a hot job in big data

The big data revolution is creating a new breed of business-IT jobs -- and threatening to destabilize dyed-in-the-wool IT careers

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"Websites used to capture only transaction data -- what was bought, who bought it, when it was shipped," he says. "Traditionally, click data was thrown away. But not anymore. The amount of data generated just by people clicking on a website is in the terabyte range. Working with lots of data can really change your business and enable you to do more and more."

Data scientists aren't just limited to social networks and data warehousing firms, says David Inbar, director of sales and marketing for Pervasive Big Data Products and Solutions, a high-performance platform provider for data-intensive analytics.

"Industries most likely to hire a data scientist are those adopting big data technologies like Hadoop, and they're everywhere -- consumer packaged goods, retail, financial services, and any company dealing with Internet-scale data," he says. "Most organizations probably haven't realized just how big the big data wave is going to be and the extent to which it will bring conventional IT architecture to its knees."

Though having some programming ability is a plus, you don't need a computer science degree to become a data scientist, Goldman says. Likewise, familiarity with statistical software packages like R or SAS is helpful, but intense curiosity and the ability to effectively present your results is just as important.

"One of the persons I hired at LinkedIn had a background in poetry," he says. "But he was very curious, asked lots of questions, and ended up doing phenomenally well."

Data visualization: The admissions officer who turned into a data wonk

When Mary Chase started her career as a college admissions officer, the job was largely about working with people to build relationships. Now it's about working with relational databases to find people.

As associate vice president for enrollment at Creighton University, Chase oversees undergraduate admissions and financial aid for the 7,000-student Jesuit school in Omaha. Since she began her career in the mid-1990s, Chase says the number of incoming applications has increased tenfold. So has the amount of information colleges request from each applicant -- from students' test scores and GPAs to their ethnic and socio-economic backgrounds, where their parents attended college, what they do for a living, and so on.

"We've had to adapt," she says. "Just using Excel is insufficient when you're looking at hundreds of thousands of student records with hundreds of data points for each. When I got into admissions work, my job was to build relationships and work with families to get them to enroll. Today it's about identifying which students we should be building relationships with and whether they fit the institution we are working for. I needed to find tools that would let me visualize data in a meaningful way."

About three years ago, Creighton adopted Tableau, a data visualization tool that hooks into the university's CRM suite and allows users to manipulate information on the fly. Using Tableau on her iPad, for example, Chase can sit in a meeting and instantly model what effect raising tuition by 3 or 4 percent would have on admissions or how that would impact the university's financial aid programs.

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