Data-Centric Intel Analysis

3 Credits · Level: Graduate

A day in the life of intelligence analysis varies widely across disciplines, organizations, and missions. However, the work of intelligence analysts everywhere is increasingly resembling that of data scientists. The change has been driven by technical advances in sensors and data infrastructure, as well as the changes in analytic problems. While this ‘big data’ environment brings greater potential for analysts to discover answers to their questions, it brings even greater challenges, too. Effective use of ‘big data’ requires constantly learning about new sensor collection, new analytic software, new visualizations techniques, keeping up with data management, and data capture. This course will begin with the history and implications of the evolution of intelligence analysis as data science. We will then cover a variety of data science concepts and skills and their application within intelligence analysis. This course will not make students data scientists, but will provide a deep appreciation for those skills as well as the foundations and a road map for pursuing them in the field in intelligence. In addition to learning concepts, history, and methods of data-centric intelligence analysis, students will in engage in the practical application of analyzing large, diverse sensor data to solve a realistic analytic challenge.