Kathy Laskey, Ph.D., et. al.
Data analytics (i.e., the process of acquiring, extracting, integrating, transforming, and modeling data with the goal of deriving useful information) is increasingly important across a wide variety of applications. The need for data analytics is driven by the massive accumulation of “Big Data” in a variety of industries such as healthcare, finance, government (federal, state, and local), and cyber defense. The ultimate goal of data analytics is to derive value by suggesting effective actions for the future. Prescriptive analytics focuses on methods for deciding on the best course of action, while taking into account constraints and risks. This tutorial in prescriptive analytics will introduce methods to drive effective decision making and to identify and select optimal courses of action. Techniques are discussed to analyze both structured and unstructured data to derive meaningful knowledge, which will be useful for developing effective strategies and making optimal decisions. The use of prescriptive analytic methods in computerized decision support systems is also discussed. The tutorial emphasizes both analytical and practical aspects of prescriptive analytics. Hands-on exercises stress the practical aspects of modeling, optimization, and risk analysis. Students are also expected to demonstrate proficiency in decision making, design of decision support systems, and risk analysis.