Tutorial on Business Intelligence

Event Detail

General Information
Dates:
Tuesday, September 6, 2005 - Tuesday, September 6, 2005
Days of Week:
Tuesday
Target Audience:
Academic and Practice
Location:
Bremen, Germany
Sponsor:
Event Details/Other Comments:

Tutorial on Business Intelligence
held by
Prof. Dr. David Hand, Imperial College London on September 6, 2005 in Bremen
The tutorial provides the opportunity to discuss in person with David Hand, one of the world's leading experts in the field of data mining and business intelligence. He has published 23 books on statistics and related areas, including Intelligent Data Analysis, Principles of Data Mining, Statistics in Finance and Measurement Theory in practice. He is a member of a number of editorial boards and was awarded a number of prizes, among them the Thomas L. Saaty Prize for Applied Advances in the Mathematical and Management Science in 2001. David Hand acts as a consultant to a wide range of organisations, including governments, banks, pharmaceutical companies, manufacturing industry and health service providers.
We are pleased to invite You to attend the tutorial which will describe and illustrate modern tools for extracting information and knowledge from data. The personal banking sector will be used as a running example of an application domain. You will learn about the latest scientific developments at the intersection of statistics, computer science and operations research and gain insight into a new perspective for these fields. David Hand will also help you to get a deeper insight into the upcoming business changes implied by data mining and to get to know the potential of business intelligence.
Program:
9.00 - 10.30 Introduction: Evidence, quantification and decision making 11.00 - 12.30 Model building. descriptive and predictive models to summarise and use business data effectively 13.30 - 15.00 Pattern discovery and pattern matching. Examples of anomaly detection in databases. Association analysis 15.30 - 17.00 Other topics. Including data quality, selectivity bias, controlled experimentation, assessment and evaluation, etc.