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DB 430: Data Warehousing and Data Mining (2+1)
Class:
BIT 9-AB
Semester:
Fall 2010
Instructor:
Email:
Website:
Office:
Extension:
Room No. 104
2161
Counseling Hours:
Posted on LMS, or by appointment.
Pre-requisites:
Introduction to Database Systems (DB-201)
Course
Description:
This course gives an overview of fundamental data warehousing concepts, in
both business and technical terms. It introduces the concepts and strategies
necessary to build a data warehouse and data mining techniques to analyze the
data in a data warehouse. Topics include Data Warehousing Concepts, Design and
Development, Extraction, Transformation and Loading, OLAP Technology, Data
Mining Techniques: Classification, Clustering and Decision Tree, Advanced Topics.
Outcomes:
After completing this course, student will be able to:
1. Demonstrate an understanding of online analytical processing and data
warehouse systems.
2. Describe methods and tools for accessing, analyzing and implementing
data warehouse.
3. Differentiate between a data warehouses OLAP and operational
databases OLTP,
4. Describe and use techniques for data extraction, transformation, and
loading,
5. Use conceptual modeling techniques to transform the business model
into a dimensional model.
6. Transform the dimensional model into a physical data design.
7. Use data mining visualization and exploratory analysis in discovery and
decision support processes.
8. Apply classification and clustering techniques for data mining.
Outcomes
Assessment:
Outcomes 2, 3, 4, 5 and 6 will be assessed through exams, quizzes and
assignments.
Outcomes 1, 7 and 8 will be assessed through exams and labs/project.
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