Module Code
SENG9240

Module Type
Option

ECTS Points
5

Duration
1 Semester

Contact Hours

3 hours per week

Pre-requisites Advanced Database Applications for Knowledge Management

Business systems intelligence is an area of increasing importance and interest to organisation involved in knowledge management. Technologies such as data warehousing and data mining offer huge potential in the creation of new knowledge products and services and the enhancement of existing products and services. The module builds on the student’s previous experiences of working with databases, knowledge tools, techniques and knowledge analysis. This module covers topics in business systems intelligence relating to the formulation of data and business models for understanding data, construction of data warehouses and the application of data mining techniques.

The module aim is to study and practise advanced data modelling techniques and to understand and practice , techniques of data warehousing and data mining in the context of knowledge management.

Kimball & Ross, 2002, Top of FormTTThe Data Warehouse Toolkit: The Complete Guide to Dimensional Modeling (Second Edition) ,Wiley

Efraim Turban and Jay E Aronson, 2001, Decision Support Systems and Intelligent Systems (6th Edition), Prentice Hall

Witten & Eibe, 1999, Data Mining: Practical Machine Learning Tools and Techniques with Java Implementations,  Morgan Kaufmann

Michael J. A. Berry, Gordon Linoff, 1997,Data Mining Techniques: For Marketing, Sales, and Customer Support, Wiley

Richard J. Roiger, Michael Gaetz, 2002, Data mining : a tutorial-based primer, Addison Wesley

Olivia Parr Rud, 2000, Data mining cookbook : modeling data for marketing, risk and customer relationship management, Wiley

Web Reference

Research Papers

• Kimball, 1997, Dimensional Modelling Manifesto, DBMS Magazine

• Fayyad, 1996, From Data Mining to Knowledge Discovery in Data, AI Magazine

Journals

• DBMS magazine, http://www.dbmsmag.com