||Alternative title: Business Intelligence with Data Mining
”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 the January 2006 Harvard Business Review
issue, Professor Thomas Davenport and colleagues document the emergence of a new
form of competition based on the extensive use of analytics, data, and
fact-based decision making. In virtually every industry, the authors found 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. Extensive interviews with
executives from successful firms show that companies today require decision
makers who 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
This course provides a comprehensive introduction to data mining problems and tools that can serve you as managers at all levels of the organization and across business units. We discuss specific scenarios, including the use of data mining to support decisions in customer relationship management (CRM), the entertainment industry, financial trading, and professional sports teams.
The three main goals of the course are to enable managers 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. Have some hands-on experience so as to follow up on ideas or opportunities that present themselves.
The course is designed for students with various backgrounds -- the class does not require any technical skills or prior knowledge.