CSCI 6405 - Data Mining and Data Warehousing
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ECMM 6014 - Databases, Data Warehouses and Data Mining for Electronic Commerce
| Time: || Tuesdays and Thursdays, 10:05-11:25 |
| Location: || McCain Arts and Social Sciences, room 2017 |
| Instructor: ||Vlado Keselj,
office: CS bldg 213,
e-mail: vlado @ cs. dal. ca
| TA: || ChunMei (May) Gao, email: cgao @ cs. dal. ca|
| Newsgroup: || dal.csci.csci6405
- CSCI 6405.03 : Data Mining and Data Warehousing
This class gives a basic exposition of the goals and methods of data
mining and data warehouses, including concepts, principles,
architectures, algorithms, implementations, and applications. The main
topics include an overview of databases, data warehouses and data
mining technology, data warehousing and on line analytical process
(OLAP), concept mining, association mining, classification and
predication, and clustering.
Software tools for data mining and data warehousing and their design
will also be introduced.
to calendar description)
- ECMM 6014.03 : Databases, Data Warehouses and Data Mining for
Data warehousing and data mining are two emerging technologies which
will have a profound effect on the role information plays in
organizations. A data warehouse is a repository of data taken from
multiple sources that supports querying and analysis tools. Data
mining, the process of knowledge discovery from data in a data
warehouse, is typically used for strategic planning and has great
economic potential for organizations.
This class covers key issues in data warehouse architecture, design of
data warehouse schemas, design of metadata repositories, the creation,
development and maintenance of warehouses, as well as tools and
techniques for querying, analyzing and mining the warehouse data. Data
mining techniques such as statistical and non-statistical supervised
and unsupervised learning methods will be applied to problems drawn
from the medical and business world.
to calendar description)
| 30% || 3 Assignments|
| 10% || Project Presentation and Class Participation |
| 30% || Project Report (Project Guide)
| 30% || Final exam|
Review Questions for the final exam
Data Mining - Concepts and Techniques by
Jiawei Han and Micheline Kamber, Morgan Kaufmann, 2001, ISBN 1-55860-489-8, http://www-faculty.cs.uiuc.edu/~hanj/DM_Book.html.
|Recommended Textbooks:|| |
Data Mining - Introductory and Advanced Topics by
Margaret H. Dunham, Prentice Hall, 2003, ISBN 0-13-088892-3.
Principles of Data Mining by
D. Hand, H. Mannila, and P. Smyth, MIT Press, 2001.
|Related Books:|| |
Data Mining - A tutorial-based primer by
Richard J. Roiger and Michael W. Geatz, Addison Wesley, 2003, ISBN 0-201-74128-8.
Data Mining - Building Competitive Advantage by
Robert Groth, Prentice Hall, 2000, ISBN 0-13-086271-1.
Modern Data Warehousing, Mining and Visualization by
George M. Marakas, Prentice Hall, 2002, ISBN 0-13-101459-5.
© 2003 Vlado Keselj, last update: April 3, 2003.