This interdisciplinary program covers fundamental concepts and tools needed for understanding business analytics in organizations, with focus on data and models to explain the performance of a business and to inform business decisions and actions. Topics include regression methods (least squares, polynomial, parameter estimation, confidence intervals, tests of hypotheses, etc.), data analytics (pre-processing, analytical methods, multi-dimensionality, knowledge discovery, visualization, clustering, forecasting, descriptive analytics, decision support, intelligent systems), and application of these analytics (classification, multi-criteria decision making, neural network, recommender systems, etc.). The program also covers big data analysis, including big data collection, preparation, preprocessing, warehousing, interactive visualization, analysis, scrubbing, mining, management, modeling, and tools such as Hadoop, Map-Reduce, Apache Spark, etc. Students apply these concepts to relevant business examples.