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From the Editors: Can a data scientist save your 'big data' project?

Collecting "big data" is easy; analyzing it can cause headaches. But some companies are turning to an emerging position, the data scientist, to help them sift through their heaps of data.

At SAS Institute's Analytics 2011 Conference Series in Orlando late last month, the "big data" conversation was unavoidable. Sessions focused on making better use of data stores by analyzing at a granular level and adding more data, such as social media information, onto the analytics plate.

To meet the challenges posed by big data sets, SAS, in partnership with Teradata and EMC Greenplum, announced a soon-to-be released high-performance computing appliance.

"We're going all in," said Radhika Kulkarni, vice president of advanced analytics research and development at SAS. By doing so, the software company will join the ranks of Oracle, SAP and Microsoft, vendors that have released products with a big-data tagline in the last six months.

Collecting reams of data is the easy part. Turning the data into actionable insight is what's causing the headaches. By 2018, the U.S. could face a talent deficit of 140,000 to 190,000 people with deep analytical skills, according to a frequently referenced May 2011 report by McKinsey & Co.

An emerging title and job category -- frowned upon by some but embraced by others -- may just provide the employees who will fill the gap. The "data scientist" is gaining popularity at companies such as Google, Groupon, LinkedIn and Facebook. Those organizations, which actively advertise their data scientist openings, are seeking out highly skilled employees to dive into data and find patterns that will have a positive business impact.

Where are you with big data? Are you facing it head-on or still scratching your head at where to begin? Let me know your thoughts and your comments may appear in an upcoming news article.

Twitter: BizAnalytics_TT

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