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Graduate Course Proposal Form Submission Detail - ISM6201
Tracking Number - 1667

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Current Status: Approved, Permanent Archive - 2007-06-21
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Detail Information

  1. Date & Time Submitted: 2007-03-27
  2. Department: IS/DS Department
  3. College: BA
  4. Budget Account Number: 1407-000-00
  5. Contact Person: Joan Moceri
  6. Phone: 9747770
  7. Email: jmoceri@coba.usf.edu
  8. Prefix: ISM
  9. Number: 6201
  10. Full Title: Data Warehousing
  11. Credit Hours: 3
  12. Section Type: C - Class Lecture (Primarily)
  13. Is the course title variable?: N
  14. Is a permit required for registration?: N
  15. Are the credit hours variable?: N
  16. Is this course repeatable?:
  17. If repeatable, how many times?: 0
  18. Abbreviated Title (30 characters maximum): Data Warehousing
  19. Course Online?: -
  20. Percentage Online:
  21. Grading Option: R - Regular
  22. Prerequisites: As a prerequisite, students should have had at least two courses covering relational database systems (usually including ISM 6218: Advanced Database Systems), or significant work experience.
  23. Corequisites:
  24. Course Description: This course is designed for the MS graduate student and interested MBA students. The course covers the rapidly emerging data warehousing and data mining technologies that are likely to play a strategic role in business organizations.

  25. Please briefly explain why it is necessary and/or desirable to add this course: Data warehouses provide the infrastructure for emerging business intelligence techniques, including navigation through online analytic processing (OLAP) interfaces and more automated data mining techniques. Graduate business students should be familiar w
  26. What is the need or demand for this course? (Indicate if this course is part of a required sequence in the major.) What other programs would this course service? This course serves as a component in the data and knowledge management course sequence in the ISDS/COBA Master of Science program. The three-course package of Advanced Database Systems, Data Warehousing, and Data Mining provide the student with detailed technical coverage of current business intelligence issues, along with the skills necessary to create an effective information infrastructure.
  27. Has this course been offered as Selected Topics/Experimental Topics course? If yes, how many times? The Data Warehousing course has been offered each fall (1998-2006), a total of nine times.
  28. What qualifications for training and/or experience are necessary to teach this course? (List minimum qualifications for the instructor.) An instructor for Data Warehousing should have a strong database background, along with knowledge of dimensional modeling and data warehouse design techniques. In addition, the instructor should be familiar with one or more state-of-the-art data warehousing systems, typically offered by leading database vendors, to offer a project-based experience. This includes knowledge of the database engine and presentation technologies like online analytic processing (OLAP) tools.
  29. Objectives: The objectives of the course are: 1) to introduce students to important aspects of enterprise-class data infrastructure technologies, 2) to review data warehousing design approaches (and case studies) 3) to introduce presentation technologies such as online analytic processing (OLAP) tools, and 4) to provide hands-on experience with enterprise-class tools for data warehouse development.
  30. Learning Outcomes: Students who complete this course will be able to: 1) identify opportunities for using data warehousing technologies, 2) be more effective team members on such projects, 3) write analytic queries using SQL and other tools, 4) be able to design data warehouses and dimensional models, and 5) be familiar with the tools to develop and administer data warehouses.
  31. Major Topics: The major course topics include an overview of business intelligence technologies, data warehouse design and dimensional modeling, analytic SQL queries, interface design using online analytic processing (OLAP) tools, administering and tuning the data warehouse, data quality, and project management issues.
  32. Textbooks: Required Text: Kimball, Reeves, Ross, Thornthwaite, The Data Warehouse Lifecycle Toolkit, John Wiley & Sons, 1998.
  33. Course Readings, Online Resources, and Other Purchases:
  34. Student Expectations/Requirements and Grading Policy:
  35. Assignments, Exams and Tests:
  36. Attendance Policy:
  37. Policy on Make-up Work:
  38. Program This Course Supports:
  39. Course Concurrence Information:


- if you have questions about any of these fields, please contact chinescobb@grad.usf.edu or joe@grad.usf.edu.