Maytal Saar-Tsechansky  
 

Assistant Professor                                                                                
Information, Risk and Operations Management                                         
McCombs School of Business                                                                    

CBA, 5.254                                                                                         
Austin, Texas 78712

Phone: (512) 471-1512 

Fax     : (212) 471-0587
 





 
Data Mining

MIS 382N.9 / MKT 382
TTh 11-12:30 PM

 
 
  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 sports teams.

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.