Big data describes collections of digital data that are too large and complicated to analyze and process with traditional software. In the government, this comes in many forms, from claims filed by Medicare beneficiaries to the video footage that military intelligence systems collect on the battlefield.
Central to the TechAmerica group’s findings is that the federal government already has much of the data and can focus mostly on training workers to analyze it.
Steve Lucas, global executive vice president of SAP’s database and technology business and co-chairman of the commission, said there is a benefit in how much cheaper the needed technology has become. A key driver “is just the dramatic reduction in the cost of computing and of storage,” he said.
What the federal government needs to improve, however, is the workforce’s skills to analyze the data, said Steven A. Mills, senior vice president and group executive for software and systems at IBM and the commission’s co-chairman.
Among the group’s recommendations are that agencies identify specific big-data projects and that the federal government establish internship programs focused on data analytics for college students. The report also recommends that the federal government create a “leadership academy” to provide big-data training and certification and that agencies name “chief data officers.”
Mills said that federal agencies likely will need to work with private companies but will be able to use cheaper, already developed technology.
“The good news is that the government doesn’t have to plow money into pure research in order to achieve results, because the commercial, off-the-shelf technology has become so robust,” he said.
The TechAmerica Foundation, which is nonprofit and nonpartisan, produces research on the technology industry and has previously convened other commissions, such as one focused on the government’s adoption of cloud computing.
The White House has said it plans to invest in making better use of the government’s data. Earlier this year, it announced a $200 million big-data initiative, including a National Institutes of Health project meant to make human genetic data more publicly accessible.