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OPEN SOURCE BIG DATA
PEO EIS and ARCYBER found something interesting in analyzing the government’s of f- the-shelf big data systems: Nearly all are built using high-quality, open- source sof tware. With a similar, government -owned platform, DOD would no longer pay high licensing fees. It could increase the competitive playing field and make all of its big data analytics work together.
by Maj. Isaac J. Faber and Ms. Elissa Zadrozny B
ig data analytics—the process of examining massive data sets containing a variety of data types to uncover hidden patterns, correlations and other stra- tegic business and operational information—is among the hottest trends in information technology and one of the Army’s highest priorities. Te Army
chief information officer/G-6 (CIO/G-6), in releasing the Army Data Strategy in Feb- ruary 2016, stated, “Te Army will utilize a two-pronged approach for managing big data. First, the Army will redouble its efforts to implement effective data management methodologies to ensure that data are authoritative, timely, secure and of the highest quality. Second, the Army will develop a process for the identification, development and implementation of efficient decision support and analytical tools to best maximize the use of information derived from big data extrapolation.”
Toward this end, the Program Executive Office for Enterprise Information Systems (PEO EIS) and the U.S. Army Cyber Command (ARCYBER) have been piloting a government off-the-shelf (GOTS), open-source platform based on open-source soft- ware and open standards. Tis effort is intended to potentially inform the way ahead.
Te Army CIO/G-6 understands that Army data scientists, technologists and acquisi- tion professionals need to work together and focus on identifying the best and most efficient ways to partner with industry to help the Army realize the promise of big data.
ASC.ARMY.MIL 105
BBP 3.0
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