Analytics is not a new invention, but rather a coming together of several technologies and fields of science including data warehousing and management, data mining, statistical modeling, forecasting, optimization, and most importantly management decision making under uncertainty.


In this course we first discuss predictive analytics that provides techniques to model the relationships between inputs and outcomes, and construct predictions about future outcomes. Then, we cover the prescriptive analytics that provides tools to optimize actions against a complex set of objectives to find best practices and design best policies under all circumstances. We also look at practical problems, solution techniques, and algorithms. Specifically, we look at examples in supply chains, service industries, healthcare systems, revenue management, inventory management, and sports. Finally, we apply our knowledge to investigate several case studies concerning real world problems and learn from a couple of guest speakers who discusses interesting challenges and opportunities that data analytics has presented.