Business Intelligence using Data Mining (BIDM) is a post-graduate elective course @ISB. The course covers 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, and clustering. We use state-of-the-art software such as Spotfire, XLMiner and Spotfire Miner, and the textbook Data Mining for Business Intelligence. 

During the 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 projects of past students.

Familiarity with data mining and business intelligence is highly sought-after in today's competitive market. This course will give you an appreciation and experience in deriving value from data.

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

Other Business Analytics elective courses at ISB that fit well with BIDM:

• Database Marketing
• Trading Strategies and Systems - This course teaches how to build and implement systematic computer-based models for trading. BIDM methods and approaches are highly synergistic.
• Business Forecasting - This course complements BIDM by focusing on forecasting time series data, which are common in many business areas and across different business functions (forecasting sales, workload, demand, inventory, etc.). The course equipts participants with statistical and data mining forecasting methods and approaches.

To get a better feel for what business analytics are about, and their value in today's business environment, watch Prof Ram Gopal interviewing Prof Galit Shmueli in July 2011

"I’ve been working for [a large] Bank for a year now, and my role recently switched into a more analytical one, requiring lots more data mining. I’m pretty sure it was because of your class that I got this role in the first place! I’m not running data analyses myself, but I’m able to work with my analysis team very effectively because of the principles I learned in Data Mining for Business." - Tim Lewis (2010 course at Smith School of Business, University of Maryland)

"[The course] lectures made a rather theoretical subject into something really interesting. I'd never really thought about how data mining was used in businesses and the project gave me a real appreciation for how it is done." - Hussain S. Boltwala (Class of 2012, Indian School of Business)