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Decision Support Systems for Business Intelligence, Second Edition

Book Description

This book examines decision making in general, the translation of knowledge about decision making into a DSS model, and the actual programming of a DSS. In addition, it combines the theoretical underpinnings of the topic with practical application using tools and technology currently available. Topics are discussed on three levels: general theory, implications for DSS design, and code development. This approach provides readers with practical examples than can be adopted into systems design.

The Second Edition has been completely updated to reflect new technologies as well as the demands upon technology that have evolved since the publication of the First Edition in 1996. The book utilizes a combination of Dreamweaver and Cold Fusion, which are both popular software products that follow industry standards. (The First Edition utilized Level 5 Object, but all references to the software have been removed as it is not deemed a viable tool any longer.)

In light of the numerous advances in the field of DSS over the years, there are many topics throughout the book that have updated and revised. For example, data warehousing has increased substantially in importance since the First Edition, and this section has been completely revised. The topic of business intelligence has been added, and similarly, data mining coverage has been increased via additional discussion and examples. In addition, transnational corporations have become more prevalent and are addressed accordingly.

Table of Contents

  1. Copyright
  2. PREFACE
    1. MAJOR FEATURES OF THE BOOK
    2. ACKNOWLEDGMENTS
  3. I. INTRODUCTION TO DECISION SUPPORT SYSTEMS
    1. 1. INTRODUCTION
      1. 1.1. WHAT IS A DSS?
      2. 1.2. USES OF A DECISION SUPPORT SYSTEM
      3. 1.3. THE BOOK
      4. 1.4. SUGGESTED READINGS
      5. 1.5. QUESTIONS
      6. 1.6. ON THE WEB
    2. 2. DECISION MAKING
      1. 2.1. RATIONAL DECISIONS
        1. 2.1.1. Bounded Rationality and Muddling Through
      2. 2.2. NATURE OF MANAGERS
      3. 2.3. APPROPRIATE DECISION SUPPORT
        1. 2.3.1. Electronic Memory
        2. 2.3.2. Bias in Decision Making
      4. 2.4. APPROPRIATE DATA SUPPORT
        1. 2.4.1. Information Processing Models
        2. 2.4.2. Tracking Experience
      5. 2.5. GROUP DECISION MAKING
      6. 2.6. INTUITION, QUALITATIVE DATA, AND DECISION MAKING
        1. 2.6.1. How Do We Support Intuition?
        2. 2.6.2. Virtual Experience
      7. 2.7. BUSINESS INTELLIGENCE AND DECISION MAKING
      8. 2.8. ANALYTICS
      9. 2.9. COMPETITIVE BUSINESS INTELLIGENCE
      10. 2.10. CONCLUSION
      11. 2.11. SUGGESTED READINGS
      12. 2.12. QUESTIONS
      13. 2.13. ON THE WEB
  4. II. DSS COMPONENTS
    1. 3. DATA COMPONENT
      1. 3.1. SPECIFIC VIEW TOWARD INCLUDED DATA
      2. 3.2. CHARACTERISTICS OF INFORMATION
        1. 3.2.1. Timeliness
        2. 3.2.2. Sufficiency
        3. 3.2.3. Level of Detail
        4. 3.2.4. Understandability
        5. 3.2.5. Freedom from Bias
        6. 3.2.6. Decision Relevance
        7. 3.2.7. Comparability
        8. 3.2.8. Reliability
        9. 3.2.9. Redundancy
        10. 3.2.10. Cost Efficiency
        11. 3.2.11. Quantifiability
        12. 3.2.12. Appropriateness of Format
        13. 3.2.13. More Is Never Better!
      3. 3.3. DATABASES
      4. 3.4. DATABASE MANAGEMENT SYSTEMS
      5. 3.5. DATA WAREHOUSES
        1. 3.5.1. Data Scrubbing
        2. 3.5.2. Data Adjustment
        3. 3.5.3. Architecture
      6. 3.6. CAR EXAMPLE
        1. 3.6.1. Possible Criteria
        2. 3.6.2. Data Warehouse
        3. 3.6.3. Information Uses
        4. 3.6.4. "How To"
      7. 3.7. DISCUSSION
      8. 3.8. SUGGESTED READINGS
      9. 3.9. QUESTIONS
      10. 3.10. ON THE WEB
    2. 4. MODEL COMPONENT
      1. 4.1. MODELS AND ANALYTICS
      2. 4.2. OPTIONS FOR MODELS
        1. 4.2.1. Representation
        2. 4.2.2. Time Dimension
        3. 4.2.3. Linearity of the Relationship
        4. 4.2.4. Deterministic Versus Stochastic
        5. 4.2.5. Descriptive Versus Normative
        6. 4.2.6. Causality Versus Correlation
        7. 4.2.7. Methodology Dimension
      3. 4.3. PROBLEMS OF MODELS
      4. 4.4. DATA MINING
        1. 4.4.1. Intelligent Agents
      5. 4.5. MODEL-BASED MANAGEMENT SYSTEMS
        1. 4.5.1. Easy Access to Models
        2. 4.5.2. Understandability of Results
        3. 4.5.3. Integrating Models
        4. 4.5.4. Sensitivity of a Decision
        5. 4.5.5. Model Management Support Tools
      6. 4.6. CAR EXAMPLE
        1. 4.6.1. Brainstorming and Alternative Generation
        2. 4.6.2. Flexibility Concerns
        3. 4.6.3. Evaluating Alternatives
        4. 4.6.4. Running External Models
      7. 4.7. DISCUSSION
      8. 4.8. SUGGESTED READINGS
      9. 4.9. QUESTIONS
      10. 4.10. ON THE WEB
    3. 4S. INTELLIGENCE AND DECISION SUPPORT SYSTEMS
      1. 4S.1. PROGRAMMING REASONING
        1. 4S.1.1. Backward-Chaining Reasoning
        2. 4S.1.2. Forward-Chaining Reasoning
        3. 4S.1.3. Comparison of Reasoning Processes
      2. 4S.2. UNCERTAINTY
        1. 4S.2.1. Representing Uncertainty with Probability Theory
        2. 4S.2.2. Representing Uncertainty with Certainty Factors
      3. 4S.3. DISCUSSION
      4. 4S.4. SUGGESTED READINGS
      5. 4S.5. QUESTIONS
      6. 4S.6. ON THE WEB
    4. 5. USER INTERFACE
      1. 5.1. GOALS OF THE USER INTERFACE
      2. 5.2. MECHANISMS OF USER INTERFACES
      3. 5.3. USER INTERFACE COMPONENTS
        1. 5.3.1. Action Language
          1. 5.3.1.1. Menus.
          2. 5.3.1.2. Question–Answer Format.
          3. 5.3.1.3. Command Language.
          4. 5.3.1.4. Input–Output Structured Formats.
          5. 5.3.1.5. Free-Form Natural Language.
        2. 5.3.2. Display or Presentation Language
          1. 5.3.2.1. Visual Design Issues.
          2. 5.3.2.2. Windowing.
          3. 5.3.2.3. Representations.
          4. 5.3.2.4. Perceived Ownership of Analyses.
          5. 5.3.2.5. Graphs and Bias.
          6. 5.3.2.6. Support for All Phases of Decision Making.
        3. 5.3.3. Knowledge Base
          1. 5.3.3.1. Modes of Communication.
      4. 5.4. CAR EXAMPLE
      5. 5.5. DISCUSSION
      6. 5.6. SUGGESTED READINGS
      7. 5.7. QUESTIONS
      8. 5.8. ON THE WEB
  5. III. Issues of Design
    1. 6. INTERNATIONAL DECISION SUPPORT SYSTEMS
      1. 6.1. INFORMATION AVAILABILITY STANDARDS
        1. 6.1.1. Data Privacy
        2. 6.1.2. Data Availability
        3. 6.1.3. Data Flow
      2. 6.2. CROSS-CULTURAL MODELING
      3. 6.3. EFFECTS OF CULTURE ON DECISION SUPPORT SYSTEM
      4. 6.4. DISCUSSION
      5. 6.5. SUGGESTED READINGS
      6. 6.6. QUESTIONS
      7. 6.7. ON THE WEB
    2. 7. DESIGNING A DECISION SUPPORT SYSTEM
      1. 7.1. PLANNING FOR DECISION SUPPORT SYSTEMS
        1. 7.1.1. Designing a Specific DSS
          1. 7.1.1.1. Interviewing Techniques.
          2. 7.1.1.2. Other Techniques.
          3. 7.1.1.3. Influence Diagrams.
          4. 7.1.1.4. Situational Analysis.
        2. 7.1.2. Design Approaches
          1. 7.1.2.1. Systems Built from Scratch.
          2. 7.1.2.2. Using Technology to Form the Basis of the DSS.
            1. 7.1.2.2.1. Evaluating a DSS Appliance.
            2. 7.1.2.2.2. Using a DSS Appliance.
        3. 7.1.3. The Design Team
      2. 7.2. DSS DESIGN AND REENGINEERING
      3. 7.3. DISCUSSION
      4. 7.4. SUGGESTED READINGS
      5. 7.5. QUESTIONS
      6. 7.6. ON THE WEB
    3. 8. OBJECT-ORIENTED TECHNOLOGIES AND DSS DESIGN
      1. 8.1. KINDS OF DEVELOPMENT TOOLS
        1. 8.1.1. Non-Object-Oriented Tools
        2. 8.1.2. Object-Oriented Tools
          1. 8.1.2.1. Defining Objects.
          2. 8.1.2.2. Attributes and Methods.
          3. 8.1.2.3. Inheritance.
          4. 8.1.2.4. Facets.
      2. 8.2. BENEFITS OF OBJECT-ORIENTED TECHNOLOGIES FOR DSS
      3. 8.3. SUGGESTED READINGS
      4. 8.4. QUESTIONS
      5. 8.5. ON THE WEB
    4. 9. IMPLEMENTATION AND EVALUATION
      1. 9.1. IMPLEMENTATION STRATEGY
        1. 9.1.1. Ensure System Does What It Is Supposed To Do the Way It Is Supposed To Do It
          1. 9.1.1.1. Prototypes.
          2. 9.1.1.2. Interviewing.
        2. 9.1.2. Keep Solution Simple
        3. 9.1.3. Develop Satisfactory Support Base
          1. 9.1.3.1. User Involvement.
          2. 9.1.3.2. Commitment to Change.
          3. 9.1.3.3. Managing Change.
        4. 9.1.4. Institutionalize System
      2. 9.2. IMPLEMENTATION AND SYSTEM EVALUATION
        1. 9.2.1. Technical Appropriateness
        2. 9.2.2. Overall Usefulness
        3. 9.2.3. Implementation Success
          1. 9.2.3.1. Measurement Challenges.
        4. 9.2.4. Organizational Appropriateness
      3. 9.3. DISCUSSION
      4. 9.4. SUGGESTED READINGS
      5. 9.5. QUESTIONS
      6. 9.6. ON THE WEB
  6. IV. Extensions of Decision Support Systems
    1. 10. EXECUTIVE INFORMATION AND DASHBOARDS
      1. 10.1. KPIs and Balanced Scoreboards
        1. 10.1.1. KPIs and Balanced Scoreboards
        2. 10.1.2. Dashboards
        3. 10.1.3. Dashboard as Driver to EIS
        4. 10.1.4. Design Requirements for Dashboard
        5. 10.1.5. Dashboard Appliances
        6. 10.1.6. Value of Dashboard and EIS
      2. 10.2. DISCUSSION
      3. 10.3. SUGGESTED READINGS
      4. 10.4. QUESTIONS
      5. 10.5. ON THE WEB
    2. 11. GROUP DECISION SUPPORT SYSTEMS
      1. 11.1. GROUPWARE
      2. 11.2. GDSS DEFINITIONS
      3. 11.3. FEATURES OF SUPPORT
        1. 11.3.1. Decision-Making Support
        2. 11.3.2. Process Support
        3. 11.3.3. GDSS and Reengineering
      4. 11.4. DISCUSSION
      5. 11.5. SUGGESTED READINGS
      6. 11.6. QUESTIONS
      7. 11.7. ON THE WEB