Close

See How Your Peers Are Moving Forward in the Cloud

New research from CDW can help you build on your success and take the next step.

Feb 12 2013
Data Analytics

Here's Why Big Data Needs Help from Data Scientists

Experts are critical to help Big Data realize its full potential.

Big Data will enable unprecedented change and progress in the federal government. However, access to the breadth of data alone won’t produce the dramatic results that Big Data can provide. Agencies must determine an effective way to analyze data and turn it into actionable intelligence.

As Big Data becomes an increasingly powerful tool, agencies must explore ways to effectively analyze and interpret this data, realizing its full potential to support missions as diverse as finding the enemy on a battlefield; improving healthcare outcomes; identifying cyber risks; reducing fraud, waste and abuse; and increasing efficiency.

As with any major mission, there are challenges, such as a lack of awareness of Big Data’s capabilities and a shortage of infrastructure. From a personnel perspective, agencies are finding that they don’t have IT workers with the necessary expertise in data science. Few have had the opportunity to gain the expertise demanded by this important role.

Finding Data Scientists

A data scientist accesses and analyzes data in order to solve problems and enact change. Data science has the capability to effectively close the gap in Big Data — helping agencies transform stationary data into actionable results. The ideal person for this role has a deep technical knowledge of data’s many applications and domain expertise in the subject at hand, as well as curiosity to discover new things. Data scientists experiment with information analytics and are an essential element in the Big Data mission.

The question agencies must ask is, “Where do we find data scientists?” People qualified for this field understand the necessary techniques and have the statistical background to make use of the deluge of data that agencies face, enabling them to mine and analyze information to determine real-life applications.

Degrees in mathematics, statistics and science, as well as database skills in software such as SQL, are desirable qualifications. Data science is emerging as a discrete specialty within computer science.

Data science curricula are growing rapidly, as seen in programs at universities such as Northwestern, North Carolina State, Stanford and the Massachusetts Institute of Technology. Additionally, there are remote learning options such as the array of online lectures produced by Associate Professor Andrew Ng of Stanford University’s Department of Computer Science.

Learn More

For more information on Big Data, check out the TechAmerica Big Data Commission’s 2012 report, Demystifying Big Data.

Individuals currently working in government — economists, mathematicians, actuaries and operations research professionals — have some of the prerequisite skills. The subject matter of their expertise isn’t as important as their background in analytics. Additional training can augment their analytical skills and prepare them for the Big Data role.

Going Forward

A recent report by the TechAmerica Foundation’s Big Data Commission included a series of recommendations related to cultivating Big Data talent in government. If implemented, the recommendations would serve as a crucial foundation. The commission recommended that the Office of Management and Budget create a formal career track in Big Data for IT managers and establish an IT Leadership Academy to provide training and certification in Big Data and related IT fields. In addition, the commission recommends that agencies cross-train IT managers to understand functional disciplines so that Big Data and related IT solutions can be effectively used to support mission goals.

Through supporting the education and training of data scientists and finding ways to bring training to current professionals who have some of the right skills, agencies will lay the foundation for real change.

<p>iStockphoto/Thinkstock</p>