TITLE: Data Warehousing and Data Mining

This course introduces the student to topics in data warehousing and data mining. With computers and databases becoming as common as paper and pencil, it is only appropriate that we be prepared to discover the knowledge hidden in the mountains of data.
 

Content Outline

Grading Procedures

Text & References

Prerequisites

1. CATALOG DESCRIPTION:
   This course provides the student with the technical skills required to plan, implement and maintain a data warehouse using appropriate software.
2. PURPOSE:
   This course introduces the student to topics in data warehousing and data mining. With computers and databases becoming as common as paper and pencil, it is only appropriate that we be prepared to discover the knowledge hidden in the mountains of data.
3. COURSE OBJECTIVES:
   The successful student will be able to:
   • Describe basic data warehousing concepts
   • Design a data warehouse
   • Gather data from primary sources, transform it and place it in a staging database
   • Create a cube using On-line analytical processing (OLAP) services
   • Analyze cube data using existing client applications
   • Maintain a data warehouse

4. CONTENT OUTLINE:

Topics of study:
• Data warehousing and Data mining
• Designing a data warehousing system
• Using the data warehouse
• Administering the warehouse
• Managing the data
• Managing the data warehouse
• Mining the data warehouse
5. INSTRUCTIONAL ACTIVITIES:
   Lectures, lab exercises
   
   
6. FIELD, CLINICAL, AND/OR LABORATORY EXPERIENCES:
None
7. RESOURCES:
   The principal resource for this course is the text.
8. GRADING PROCEDURES:
The student will be graded on the standard 60/70/80/90 scale for D/C/B/A respectively. Activities include quizzes/assignments, midterm, a term paper and a project.


9. ATTENDANCE POLICY:
   Since the grading procedure does not include attendance per se, missing one class or two during the semester will not necessarily be detrimental to your final grade.  Your ability to fare well on examinations will be greatly affected by excessive absences (greater than 10%).
10. ACADEMIC HONESTY POLICY:
    Please drop the course if you don't want to do your own work. Copying of programming assignments will NOT be tolerated. The College of Business and Public Affairs' policy on academic honesty will be strictly enforced. All infractions are immediately reported to the Dean whose actions may vary from an "E" for the course to being expelled from the school.
11. TEXT AND REFERENCES:
The Data Warehouse Toolkit, by Ralph Kimball, John Wiley and Sons, 1996.
12. PREREQUISITES:
    CIS 307 or equivalent.