Section menuClose menu Columbia College

MASTER SYLLABUS

Master Syllabus

Print this Syllabus « Return to Previous Page

Administrative Unit: Computer and Mathematical Sciences Department
Course Prefix and Number: CISS 472
Course Title: Data Warehousing and Decision Support Systems
Number of:
Credit Hours 3
Lecture Hours 3
Lab Hours 0
Catalog Description: An investigation of data warehousing, data mining and decision support systems. Topics include design and architectural issues, cost effectiveness, management concerns, data integrity, deployment and maintenance issues. Prerequisite: CISS 430.
 
Prerequisite(s) / Corequisite(s): CISS 430.
 
Course Rotation for Day Program: Offered Fall.
 
Text(s): Most current editions of the following:

Decision Support Systems and Intelligent Systems
By Turban, E., et. al. (Prentice Hall)
Recommended
Data Mining: Concepts and Techniques
By Han, J., and Kamber. M. (Morgan Kaufmann)
Recommended
 
Course Objectives
  • To learn data mining and decision support fundamentals and techniques.
  • To understand data collection, cleaning and aggregation issues.
  • To construct meaningful multi-dimensional models.
  • To investigate data warehousing issues.
  • To utilize a data mining query language.
  • To learn statistical techniques for analyzing data.
  • To utilize decision trees in data analysis.
  • To investigate cluster analysis.
  •  
    Measurable Learning
    Outcomes:
  • Characterize a data warehouse.
  • Describe data warehousing architectures.
  • Discuss data clearing and reduction issues.
  • Utilize a data mining query language.
  • Employ statistical measures in data analysis.
  • Explain data mining association rules.
  • Utilize decision tree techniques for data analysis.
  • Perform cluster analysis.
  •  
    Topical Outline:
  • Data warehousing techniques and issues
  • Data preprocessing
  • Data reduction
  • Data cleaning
  • Query languages for data mining
  • Developing mining association rules
  • Data classification and prediction techniques
  • Cluster analysis
  • Ethical issues in data mining
  •  
    Culminating Experience Statement:

    Material from this course may be tested on the Major Field Test (MFT) administered during the Culminating Experience course for the degree. 
    During this course the ETS Proficiency Profile may be administered.  This 40-minute standardized test measures learning in general education courses.  The results of the tests are used by faculty to improve the general education curriculum at the College.

     

    Recommended maximum class size for this course: 20

     
    Library Resources:

    Online databases are available at http://www.ccis.edu/offices/library/index.asp. You may access them from off-campus using your CougarTrack login and password when prompted.

     
    Prepared by: Lawrence West Date: September 12, 2007
    NOTE: The intention of this master course syllabus is to provide an outline of the contents of this course, as specified by the faculty of Columbia College, regardless of who teaches the course, when it is taught, or where it is taught. Faculty members teaching this course for Columbia College are expected to facilitate learning pursuant to the course objectives and cover the subjects listed in the topical outline. However, instructors are also encouraged to cover additional topics of interest so long as those topics are relevant to the course's subject. The master syllabus is, therefore, prescriptive in nature but also allows for a diversity of individual approaches to course material.

    Office of Academic Affairs
    12/04