King Abdulaziz University, Jeddah, Saudi Arabia
CPIS-320
Decision Support Systems and Theory
Course Syllabus
Catalog Description
CPIS-320 Decision Support Systems and Theory, Credit: 3
Elective ,
Lecture: 3
Practical: 2
Training: 1
The objective of this course is to study how Decision Support Systems (DSS) work and the theory behind
different DSS techniques, thereby enabling them to understand today's turbulent business environment and
how organizations survive and even excel in such environments (particularly solving problems and
exploiting opportunities). This course provides the required skills and knowledge of the various decisionmaking models so that decisions can be based on logical and mathematical foundations under different
circumstances, such as in cases of uncertainty, lack of information, or certainty. This course studies the
design of computerized systems to support individual or organizational decisions. Moreover, the course aims
at understanding the need for computerized support of managerial decision making and what was an early
framework for managerial decision making.
Prerequisite
CPIS-250 , CPIS-220
Textbook
Turban, Ramesh Sharda, Dursun Delen, "Decision Support and Business Intelligence Systems", Prentice
Hall, 9 Edition, 2010
ISBN-13 9780136107293
ISBN-10 013610729X
Course Learning Outcomes (CLO)
By the completion of the course the students should be able to
1. Discuss today’s turbulent business environment and describe how organizations survive and even excel
in such an environment.
2. Discuss the need for computerized support of managerial decision making.
3. Describe the conceptual foundation of the decision support system (DSS) and business intelligence (BI)
methodology and relate them each other.
4. List the major tools of computerized decision support and major issues in implementing computerized
decision support systems.
5. Define the conceptual foundations of decision making.
6. Discuss Simon’s four phases of decision making: Intelligence, Design, Choice, and Implementation.
7. Compare between the concepts of making a choice and establishing a principle of choice.
8. Discuss in group using their own experience about DSS issues, and implementation in today’s business
environment.
9. Describe the key differences and similarities between DSS and BI systems.
10. Describe DSS characteristics, capabilities and configurations.
11. Describe and develop the components and structure of each DSS components: the data management
subsystem, the model management subsystem, the user interface subsystem, and the knowledge-based
management subsystem.
12. Explain internet impacts on DSS and vice versa also describe DSS hardware and software platforms and
DSS modeling language: Planners Lab.
13. Describe the basic concepts of management support system modeling.
14. Describe how spreadsheet can be used of MSS modeling and solutions.
15. Explain the basic concept of optimization, simulation, linear programming and heuristic, and when to
use them using several examples.
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King Abdulaziz University, Jeddah, Saudi Arabia
CPIS-320
Decision Support Systems and Theory
Course Learning Outcomes (CLO)
By the completion of the course the students should be able to
16. Define and explain with practical example using software about, what is meant by sensitivity analysis,
what-if analysis, and goal seeking.
17. Discuss in group about “data mining as an enabling technology for business intelligence, and describe
the objective and benefits of business analytics and data mining”.
18. Cite the wide range of applications of data mining and understand the standardized data mining
processes.
19. Identify and discuss the steps involved in data preprocessing for data mining.
20. Define and discuss different methods and algorithms of data mining.
Course Topics and their Duration
Number
1
2
3
4
5
Description
Decision Support System and Business Intelligence
Decision Making, Systems, Modeling, and Support
DSS Concepts, Methodologies, and Technologies: An Overview
Modeling and Analysis
Data Warehousing
Duration in Weeks
2
2
3
3
2
Class Schedule
Lab 90 minutes 1 times/week
Meet 50 minutes 3 times/week or 80 minutes 2 times/week
Course Relationship to Key Student Outcomes
A B C D E F G H
X
I
J
X
X
Prepared By:
Dr. Farrukh Nadeem, Assistant Professor
Coordinator:
Spring 2014 (Second Term - 1434-1435 )
Dr. Abdulallah Al-Barakati, Assistant Professor
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