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George Mason University – Graduate Council Graduate Course Approval Form All courses numbered 500 or above must be submitted to the Graduate Council for final approval after approval by the sponsoring College, School or Institute. Graduate Council requires submission of this form for a new course or any change to existing courses. For a new course, please attach a copy of the syllabus and catalog description (with catalog credit format, e.g. 3:2:1). The designated representative of the College, School or Institute should forward the form along with the syllabus and catalog description, if required, as an email attachment (in one file) to the secretary of the Graduate Council. A printed copy of the form with signatures and the attachments should be brought to the Graduate Council meeting. Please complete the Graduate Course Coordinator Form if the proposed changes will affect other units. Note: Colleges, Schools or Institutes are responsible for submitting new or modified catalog descriptions (35 words or less, using catalog format) to Creative Services by deadlines outlined in the yearly Catalog production calendar. Please indicate: New____X___ Modify_______ Department/Unit: School of Management Submitted by: Roy Hinton Delete_______ Course Subject/Number: GSOM 631 Ext: 1662 Email: [email protected] Course Title: Business Intelligence and Data Mining Effective Term (New/Modified Courses only): Fall 2008 Credit Hours: (Fixed) __3___ (Var.) ______ to ______ Final Term (deleted courses only):____________ Grade Type (check one):___X__ Regular graduate (A, B, C, etc.) _____ _____ Satisfactory/No Credit only Special graduate (A, B, C, etc. + IP) Repeat Status*(check one): __X_ NR-Not repeatable ____ RD-Repeatable within degree ____ RT-Repeatable within term *Note: Used only for special topics, independent study, or internships courses Total Number of Hours Allowed: _______ Schedule Type Code(s): 1. LEC LEC=Lecture SEM=Seminar STU=Studio INT=Internship IND=Independent Study 2. ___ LAB=Lab RCT=Recitation (second code used only for courses with Lab or Rct component) Prereq __X_ Coreq ___ (Check one): Admission to a SOM graduate certificate program, admission to a graduate program in the School of Management, or written permission of the instructor. __________________________________________________________________________________________ Note: Modified courses - review prereq or coreq for necessary changes; Deleted courses - review other courses to correct prereqs that list the deleted course. Description of Modification (for modified courses):____________________________________________________________________ Special Instructions (major/college/class code restrictions, if needed):__________________________________________ Department/Unit Approval Signature:_________________________________________ Date: _____________ College/School Committee Approval Signature:__________________________________ Date:_____________ Graduate Council Approval Date:____________ Provost Office Signature:_________________________________ George Mason University Graduate Course Coordination Form Approval from other units: Please list those units outside of your own who may be affected by this new, modified, or deleted course. Each of these units must approve this change prior to its being submitted to the Graduate Council for approval. Unit: Head of Unit’s Signature: Date: Unit: Head of Unit’s Signature: Date: Unit: Head of Unit’s Signature: Date: Unit: Head of Unit’s Signature: Date: Unit: Head of Units Signature: Date: Graduate Council approval: ______________________________________________ Date: ____________ Graduate Council representative: __________________________________________ Date: ____________ Provost Office representative: ____________________________________________ Date: ____________ Catalog Description This course examines how data warehouses and data mining are used to help businesses successfully gather, structure, analyze, understand and act on relevant data, both operational and contextual. The components of and design issues related to data warehouses and business intelligence techniques for extracting meaningful and actionable information from data warehouses are emphasized. The course will also involve analysis and discussion of practice oriented articles in different functional areas of business. Master Syllabus GSOM 631: Business Intelligence and Data Mining Prerequisites: Admission to SBI graduate certificate program or written permission of instructor; MBA 633 or equivalent Course Description: This course examines how data warehouses and data mining are used to help businesses successfully gather, structure, analyze, understand and act on relevant data, both operational and contextual. The components of and design issues related to data warehouses and business intelligence techniques for extracting meaningful and actionable information from data warehouses are emphasized. The course will also involve analysis and discussion of practice oriented articles in different functional areas of business. Learning Objectives: Understand Business Intelligence fundamentals Understand data warehousing structure and processes Understand principles of data mining Hands on experience with selected data mining software Hands on experience with selected data warehousing software Approach to Learning: The material in this course is presented in a lecture/discussion format with liberal use of case studies. In- and out-of-class problems, cases and projects are used develop the student’s analysis skills. Hands on experience with appropriate software packages will enhance the conceptual content presented in class. Guest speakers may be invited to present and share their professional experience. Course Website: (See individual instructor syllabi for specific section addresses) Representative Text and Materials: – Kimball & Ross, The Data Warehouse Toolkit: The Complete Guide to Dimensional Modeling, Wiley, 2nd ed. 2002 – Hand, Mannila, and Smyth, Principles of Data Mining, MIT Press, 2001. – Berry and Linoff. Mastering Data Mining. Wiley, 2000 – Additional cases and readings as determined by instructor Student Responsibilities: This course covers a great deal of material in rather large chunks at a time. Students are therefore expected to stay current with their assigned readings and complete assignments in a timely manner. They are also expected to contribute to class discussions and case analyses. Students are responsible for all information posted at the course website (i.e., WebCT). Methods of Student Evaluation: Exams, case analysis (individual and group) and presentations. Students may also be required to prepare a research paper on an area of special interest to them. Course Topics – Evolution of Decision Support Systems and business intelligence fundamentals – Introduction to data warehousing and data marts – Basic elements and processes of data warehousing – Dimensional data model and its use for business analysis – Hands on experience with Microstrategy business intelligence Software – One large scale business intelligence implementation case study. – Quantitative techniques for data mining – Artificial intelligence techniques for data mining – Hands on experience with business intelligence software – Business intelligence applications in business functions – Real time warehousing and business intelligence – Data mining case studies Other topics may be added at the instructor’s discretion. Honor Code: The faculty expects students to follow the Honor Code as present in the University’s publications. ODS Statement: If you are a student with a disability and you need academic accommodations, please see the instructor and contact the Office of Disability Services (ODS) at 993-2474. All academic accommodations must be arranged through the ODS.