Course Title: Decision Support System
Course No: CSC-460 Full Marks: 60 + 20 +20
Credit Hrs: 3 Pass Marks: 20 + 8 + 8
Nature of course: Theory (3 Hrs.) + Lab (3 Hrs.)
Course Synopsis: This course covers introduction to decision support systems; DSS components; Decision making; DSS software and hardware;
developing DSS; DSS models; types of DSS; data mining; artificial intelligence and expert Systems.
Goal: The course is devoted to introduce decision support systems; show their relationship to
other computer-based information systems, demonstrate DSS development approaches,
and show students how to utilize DSS capacities to support different types of decisions.
Course Contents:
Unit 1: Decision Making and Computerized Support
1.1. Management Support Systems: An Overview 3 Hrs.
Managers and Decision-Making; Managerial Decision-Making and Information Systems; Managers and Computer Support; Computerized Decision
Support and the Supporting Technologies; A Framework for Decision Support; The Concept of Decision Support Systems; Group Support
Systems; Enterprise Information Systems; Knowledge Management Systems; Expert Systems; Artificial Neural Networks; Advanced Intelligent
Decision Support Systems; Hybrid Support Systems
1.2. Decision-Making Systems, Modeling, and Support 5 Hrs.
Decision-Making: Introduction and Definitions; Systems; Models; Phases of the Decision-Making Process; Decision-Making: The Intelligence
Phase; Decision-Making: The Design Phase; Decision-Making: The Choice Phase; Decision-Making: The Implementation Phase; How Decisions Are
Supported; Personality Types, Gender, Human Cognition, and Decision Styles; The Decision-Makers
Unit 2: Decision Support Systems
2.1. Decision Support Systems: An Overview 3 Hrs.
DSS Configurations; What Is a DSS?; Characteristics and Capabilities of DSS; Components of DSS; The Data Management Subsystem; The
Model Management Subsystem; The User Interface (Dialog) Subsystem; The Knowledge-Based Management Subsystem; The User; DSS
Hardware; DSS Classifications
2.2. Modeling and Analysis 4 Hrs.
MSS Modeling; Static and Dynamic Models; Certainty, Uncertainty, and Risk; Influence Diagrams; MSS Modeling with Spreadsheets; Decision
Analysis of a Few Alternatives (Decision Tables and Decision Trees); The Structure of MSS Mathematical Models; Mathematical Programming
Optimization; Multiple Goals, Sensitivity Analysis, What-If, and Goal Seeking; Problem-Solving Search Methods; Heuristic Programming;
Simulation; Visual Interactive Modeling and Visual Interactive Simulation; Quantitative Software Packages; Model Base Management
2.3.Business Intelligence: Data Warehousing, Data Acquisition, Data Mining, Business Analytics, and Visualization 4 Hrs.
The Nature and Sources of Data; Data Collection, Problems, and Quality; The Web/Internet and Commercial Database Services; Database
Management Systems in Decision Support Systems/ Business Intelligence; Database Organization and Structures; Data Warehousing; Data
Marts; Business Intelligence/Business Analytics; Online Analytical Processing (OLAP); Data Mining; Data Visualization, Multidimensionality, and
Real-Time Analytics; Geographic Information Systems; Business Intelligence and the Web: Web Intelligence/Web Analytics
2.4. Decision Support System Development 3 Hrs.
Introduction to DSS Development; The Traditional System Development Life Cycle; Alternative Development Methodologies; Prototyping: The
DSS Development Methodology; Change Management; DSS Technology Levels and Tools; DSS Development Platforms; DSS Development Tool
Selection; Team-Developed DSS; End User Developed DSS; Putting The DSS Together
Unit 3: Knowledge Management
3.1. Knowledge Management 5 Hrs.
Introduction to Knowledge Management; Organizational Learning and Transformation; Knowledge Management Initiatives; Approaches to
Knowledge Management; Information Technology in Knowledge Management; Knowledge Management Systems Implementation; Roles of People in
Knowledge Management; Ensuring Success of Knowledge Management
Unit 4: Intelligent Decision Support Systems
4.1. Artificial Intelligence and Expert Systems: Knowledge-Based Systems 5 Hrs.
Concepts and Definitions of Artificial Intelligence; Evolution of Artificial Intelligence; The Artificial Intelligence Field; Basic Concepts of
Expert Systems; Applications of Expert Systems; Structure of Expert Systems; How Expert Systems Work; Problem Areas Suitable for Expert
Systems; Benefits and Capabilities of Expert Systems; Problems and Limitations of Expert Systems; Expert System Success Factors; Types of
Expert Systems; Expert Systems on the Web
4.2. Knowledge Acquisition, Representation, and Reasoning 5 Hrs.
Concepts of Knowledge Engineering; Scope and Types of Knowledge; Methods of Knowledge Acquisition from Experts; Knowledge Acquisition
from Multiple Experts; Automated Knowledge Acquisition from Data and Documents; Knowledge Verification and Validation; Representation of
Knowledge; Reasoning in Rule-Based Systems; Explanation and Metaknowledge; Inferencing with Uncertainty; Expert Systems Development;
Knowledge Acquisition and the Internet
4.3. Advanced Intelligent Systems 5 Hrs.
Machine-Learning Techniques; Case-Based Reasoning; Basic Concept of Neural Computing; Learning in Artificial Neural Networks; Developing
Neural Network-Based Systems; Genetic Algorithms Fundamentals; Developing Genetic Algorithm Applications; Fuzzy Logic Fundamentals;
Developing Integrated Advanced Systems
4.4. Intelligent Systems over the Internet 3 Hrs.
Web-Based Intelligent Systems; Intelligent Agents: An Overview; Characteristics of Agents; Why Intelligent Agents?; Classification and Types
of Agents; Internet-Based Software Agents; DSS Agents and Multi-Agents; Semantic Web: Representing Knowledge for Intelligent Agents;
Web-Based Recommendation Systems; Managerial Issues of Intelligent Agents
Laboratory Work: The laboratory should contain the concepts of artificial intelligence that are
applicable to the development of decision support systems.
Reference Books:
1. Decision Support Systems and Intelligent Systems, Seventh Edition, Efraim Turban, Jay E. Aronson, Richard V. McCarthy, Prentice-Hall of
India, 2007
2. Decision Support Systems, A Knowledge-Based Approach, Clyde W. Holsapple andAndrew B. Whinston
3. Decision Support Systems For Business Intelligence by Vicki L. Sauter
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