Data Mining for Business is an MBA-level elective course. We discuss data mining techniques and their use in strategic business decision making. This is a hands-on course that provides an understanding of the key methods of data visualization, exploration, classification, prediction, time series forecasting, and clustering. We use neat software such as Spotfire, XLMiner and SAS Enterprise Miner, and the textbook Data Mining for Business Intelligence. See more details in the recent course syllabus.

Many past students say this is one of the best courses they took during their MBA, and that it has directly assisted them in job hunting and in their actual jobs.

During the semester-long course, students work in teams on solving a business problem of their choice, using data mining tools and applying them to real data. Click here to view presentations and brief reports for some of the projects.

Course veterans can join the LinkedIn Group. You're also welcome to visit my blog on Business and Statistics.

Instructors of data mining courses in business schools are welcome to join the BZST teaching forum for resource sharing.

What other MBA courses @ Smith go well with "Data Mining for Business?"? My students recommend:

• Financial Statements Analysis (BUAC 758Z): "Some of the Data Mining techniques really aligned well with my assignments in BUAC758Z... For example, the goal of our final team project was to determine
  whether we should invest in certain companies based on the
  corporation's previous financial statements and overall industry
  averages, and then to predict on how well the company would perform in
  future quarters."
• Pricing and Revenue Management (BUDT775): "If you're liking BUDT733, you'll like BUDT775."