Download MBA 738 - Office of the Provost

George Mason University
Graduate Course Approval/Inventory Form
Please complete this form and attach a copy of the syllabus for new courses. Forward it as an email attachment
to the Secretary of the Graduate Council. A printed copy of the form with signatures should be brought to the
Graduate Council Meeting. Complete the Coordinator Form on page 2, if changes in this course will affect
other units.
Please indicate:
__X__ NEW
____ MODIFY
____ DELETE
Local Unit: School of Management
Graduate Council Approval Date:
Course Abbreviation:
Course Number: 738
MBA
Full Course Title: Business Intelligence and Data Management
Abbreviated Course Title (24 characters max.): Bus Intell & Data Mgmt
Credit hours:
3
Program of Record: MBA
Repeatable for Credit?
___ D=Yes, not within same term
___ T=Yes, within the same term
_X N=Cannot be repeated for credit
Up to hours
Up to hours
Activity Code (please indicate):
_X_ Lecture (LEC) ___ Lab (LAB)
___ Recitation (RCT)
___ Studio (STU)
___ Internship (INT) ___ Independent Study (IND)
____ Seminar (SEM)
Catalog Credit Format
3:3 :0
Course Level: GF(500-600) ____
GA(700+) _X___
Maximum Enrollment: 20
For NEW courses, first term to be offered: Spring 2007
Prerequisites or corequisistes:
Completion of MBA core or permission of instructor
Catalog Description (35 words or less) Please use catalog format and attach a copy of the syllabus for new
courses.:
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
For MODIFIED or DELETED courses as appropriate:
Last term offered:
Previous Course Abbreviation:
Previous number:
Description of modification:
APPROVAL SIGNATURES:
Submitted by:
________________________________ email: ________________
Department/Program:
College Committee:
________________________________ Date: __________________
________________________________ Date: _________________
Graduate Council Representative: ________________________________ Date: __________________
GEORGE MASON UNIVERSITY
Course Coordination Form
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Unit:
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Graduate Council approval: ______________________________________________ Date: ____________
Graduate Council representative: __________________________________________ Date: ____________
Provost Office representative: _________________ _______________________
Date: __________
MBA 738: Business Intelligence and Data Management
Master Syllabus
Prerequisites: Completion of MBA core or permission of instructor
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. (3:3:0)
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:
Students are expected to follow the Honor Code as present in the University’s publications.
DRC Statement:
If you are a student with a disability and you need academic accommodations, please see the instructor and
contact the Disability Resource Center (DRC) at 993-2474. All academic accommodations must be arranged
through DRC.