This course introduces students some basic decision theory and decision analysis modeling tools. The course is opened with basic concepts in decision theory and decision analysis along with tools for model building in Excel for analyzing decision making problems in various contexts. Students will learn how to structure and analyze decision problems in a general setup. Focus is on methods that are used extensively in business to solve large problems. Methods of this type generate results that support decision-making at all levels of the organization over various time horizons. The structuring and analysis part of the course is followed by a discussion of how to integrate the relevant data in the decision-making problem with the aim of designing data driven decision models. The decision theory and decision analysis modeling ability can be applied to different business contexts, such as problems in operations management, marketing, strategic decision making, project evaluations, etc. Cases from featuring real world business scenarios are used throughout the course. The students will learn how to structure a decision-making problem and make data-driven decision analysis using decision tree and simulation techniques. The students will also study different Excel models based on simulation, decision tree analysis, optimization, and data analysis techniques, covering a few marketing and operations management problems. The students will develop skills to explore real word data or simulated data to drive business decision making with the aim of gaining new insights and understanding of business problems.