This course examines the design of databases and data warehouses and their use for data mining; and investigates associated issues. Topics may include: relational theory and conceptual modelling; privacy and security; statistical databases; distributed databases; data warehousing; data cleaning and integration; and data mining concepts and techniques.

On completion of this course, the students should have gained a good understanding of basic concepts, principles and techniques in data warehousing and data mining. Specifically, the students are able to perform the following tasks.

• Perform data modeling
• Apply OLAP techniques for mulit-dimensional data analysis
• Apply datacubing techniques
• Develop general skill of data warehousing project management
• Obtain the general knowledge on the design and implementation of data warehouses
• Be able to apply data mining techniques for knowledge discovery
• Develop in-depth understanding of fundamental data mining algorithms
• Perform data mining in data warehouses.

Two assignments (40 marks); Final Exam (60 marks)

Thirty one-hour lectures and six two-hour tutorials

COMP1100 or COMP1130 or COMP1720 or COMP1730; COMP2400; 6 units of 2000-level IT courses; and 6 units of 1000-level MATH/STAT courses.

The following text book will be used for this course:

• Jiawei Han, Micheline Kamber, and Jian Pei,Data Mining:Concepts and Techniques, 3rd edition, Morgan Kaufmann, 2011 http://www.cs.uiuc.edu/~hanj/bk3/