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IT Management Slideshow:
Big Data: Who Can Make Sense of It?

By Dennis McCafferty on 2011-12-23


The problem with big data isn’t gaining access to it – it’s knowing what to do with it once you’ve got it. To achieve this, CIOs and IT organizations depend upon the experience and skills of data scientists. These professionals are driven to analyze a mass assemblage of information to help companies achieve strategic goals. That said, a significant shortfall in data-science talent looms large, according to a global survey from EMC Corp., which has launched a training/certification program to help address this need. The world’s volume of data doubles every 18 months, according to industry forecast, fueled by a wealth of mobile sensors, social media, surveillance, medical imaging, smart grids and other information generators. This creates a dynamic in which the vast majority of data professionals doubt that companies will be able to keep up, and future business growth will suffer as a result. Nearly 500 members of the data science community -- including data specialists, business intelligence analysts and data engineers, all with IT decision-making authority -- took part in the survey, conducted by the EMC Data Science Community. For more about the survey, click here. Here are eight highlights:

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One-third


Only one-third of respondents are confident in their company’s ability to make business decisions based upon new data.

38%


38% of respondents strongly agree that their company uses data to learn more about customers.

22%


Less than a quarter of respondents strongly believe employees have access to run experiments on data. This lack of access hinders a company’s ability to test, validate and innovate.

63%


63% of respondents feel that demand for data scientists will outpace the supply of talent over the next five years.

12%


Only 12% of respondents feel the best source of new data-science talent should come from the ranks of today’s business intelligence professionals.

31%


31% of data scientists polled have a master’s or post-graduate professional degree, compared to 12% of business-intelligence professionals polled.

Best Sources of Data Science Talent (percent respondents):


Computer-science students (34%)
Professionals in disciplines other than computer science (27%)
Students studying something other than computer science (24%)

Five Biggest Obstacles to Data-Science Adoption (percent respondents)


Insufficient employee skills or training (32%)
Lack of budget or resources (32%)
Ill-fitting organizational structure (14%)
Unavailability of needed tools or technology (10%)
Inadequate executive support (9%)

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