Data analytics problem-solving strategies applied to a real-world business context. BAN 530 Business Strategies for Data Analytics (3) BAN 530 integrates the descriptive/prescriptive/predictive framework for business analytics courses and sets analytics problem solving in a real-world business context. The objective is to provide students with experience with noisy data sets, potential compliance issues, non-standard measures across business units, and other real-world considerations in using data to drive decisions. The course will examine the entire life cycle of a data analytics project, from data origination through collection, filtering, tool selection, calculation, and communication. Particular emphasis will be placed on problem formulation: identifying what the business issue is at hand, what data might be useful in understanding that issue, and what tools can be most usefully applied in a particular context. In addition, communication skills will be emphasized: how data informs the decision-making process when the audience likely lacks the specialized quantitative literacy of the project team. Other important considerations include many facets of information privacy: students will consider the ethical and legal implications of de-anonymization, of deep insight into individual behavior, and of opt-in versus opt-out models of participation.
Systematic and analytical approaches to marketing decision-making within modern day enterprises. BAN 540 Marketing Analytics (3) The course objectives are to demonstrate the benefits of using a systematic and analytical approach to marketing decision-making, and to build the skills and confidence of students for undertaking such analyses and decision-making in a modern enterprise. The analytical approaches covered in the course will enable students to identify alternative marketing options and actions that enhance business performance, predict the expected market and consumer reactions associated with potential marketing actions undertaken by a business, calibrate the opportunity costs associated with each action, and choose one or more actions that have the highest likelihood of achieving established business goals. The course will help students to develop skills that will enable them to propose and justify marketing expenditures using a Return on Investment (ROI) logic that businesses are increasingly asking of their executives. This course builds on the basic business analytics concepts and methods that business students are expected to have. The “hands-on” learning approaches used in the course (e.g., exercises and cases using real-world data) will enable students to apply course concepts and methods to develop integrated marketing programs that can be deployed across online and offline media and channels. The topics will include traditional marketing analytics such as segmentation, targeting, positioning, product design, and marketing resource allocation as well as emerging analytics such as search engine analytics, social influence measurement, and attribution analysis.
Development of methods for prescriptive analytics with a focus on business supply side decisions and risk mitigation. BAN 550 Prescriptive Analytics for Business (3) Analytics, defined as the scientific process of using data and quantitative techniques to make better decisions, has permeated virtually all aspects of business. The widespread availability of large amounts of detailed data combined with analytics methods permits an extensive examination of the tradeoffs that inform business decision making, with the ultimate goal of choosing “best” courses of action. BAN 550 explores the use of prescriptive analytics methods in a variety of business contexts. In the early part of the course, the focus is on the tools and methods of prescriptive analytics. As the course progresses the emphasis shifts to the effective integration and implementation of prescriptive analytics in supply-side decision making processes such as supply chain management, service management, operations, logistics and transportation. The applications areas within business will reflect the interests of the instructors and will evolve as new areas of theory and practice develop.
Prerequisite: BAN 540
Sets business analytics in real-world context. Explores project life cycle from business problem framing to model lifecycle management. BAN 888 Implementing Analytics for Business (3) The capstone course for the Business Analytics option in the Data Analytics MPS degree program, this course sets analytics problem solving in a real-world context, including communication to non-statistically trained executives. Key topical areas are derived from the common activities of the business analyst and include business problem framing, analytics problem framing, data sourcing, cleaning and integration, analysis methodology selection, model building, model deployment and model lifecycle management including benefit assessment. Topics align with the body of knowledge in the Institute for Operations Research and the Management Sciences (INFORMS) Certified Analytics Professional Study Guide. Students explore each topic in a real world context, by developing solutions to cases in a team setting. Each team selects a case and works through all elements of the analytics body of knowledge, with group presentations on problem framing, analytics model selection and development, and model lifecycle management in a business setting.
Prerequisite: BAN 530 and BAN 550