Prerequisite: Admissions to a Business Major, Upper division standing and MKT 337 or MKT 337H. Additional Prerequisite: STA 309 or 309H
”For every leader in the company, not just for me, there are decisions that can be made by analysis. These are the best kinds of decisions. They’re fact-based decisions.” Amazon’s CEO, Jeff Bezos.
In virtually every industry, the competitive strategies organizations are employing today rely extensively on data analysis to predict the consequences of alternative courses of action, and to guide executive decision making, more generally. Companies today are competing on analytical capabilities and require analysts and decision makers who both understand the value of analytics, can identify opportunities and know how best to apply data analytics to enhance business performance. The spreading of analytical competition spans industries—from consumer finance to retailing to travel and entertainment to consumer good, and even professional sports teams.
This course provides a comprehensive introduction to data mining problems and tools to enhance managerial decision making at all levels of the organization and across business units. We discuss scenarios from a variety of business disciplines, including the use of data mining to support customer relationship management (CRM) decisions, decisions in the entertainment industry, financial trading, and even professional sports teams.
The three main goals of the course are to enable students to:
1. Approach business problems data-analytically by identifying opportunities to derive business value from data mining.
2. Interact competently on the topic of data-driven business intelligence (know the basics of data mining techniques and how they can be applied to extract relevant business intelligence.)
3. Acquire some hands-on experience so as to follow up on ideas or opportunities that present themselves.
The course is specifically designed for students with various backgrounds -- the class does not require any technical skills or prior knowledge.