You are previewing Principles and Applications of Business Intelligence Research.
O'Reilly logo
Principles and Applications of Business Intelligence Research

Book Description

Utilizing technologies, processes, and applications to analyze internal and structured data, business intelligence is a key aspect in the ability of an organization to gather knowledge and develop new opportunities for growth. Principles and Applications of Business Intelligence Research provides the latest ideas and research on the practices and management of business intelligence. Including original research, case studies, and analysis, this comprehensive collection aims to advance the understanding and implementation of business intelligence. 

Table of Contents

  1. Cover
  2. Title Page
  3. Copyright Page
  4. Editorial Advisory Board and List of Reviewers
    1. Associate Editors
    2. List of Reviewers
  5. Preface
    1. INTRODUCTION
    2. ORGANIZATIONAL ISSUES
    3. ANALYTIC ISSUES
    4. TECHNOLOGY ISSUES
  6. Section 1: Organizational Issues
    1. Chapter 1: Using Business Intelligence in College Admissions
      1. ABSTRACT
      2. INTRODUCTION
      3. PURPOSE OF THE STUDY
      4. STUDY DESIGN AND METHODOLOGY
      5. DATA COLLECTION AND ANALYSIS
      6. SIGNIFICANCE AND LIMITATIONS
      7. LITERATURE REVIEW
      8. DATA ANALYSIS
      9. SUMMARY AND CONCLUSION
    2. Chapter 2: Anticipatory Standards Development and Competitive Intelligence
      1. ABSTRACT
      2. INTRODUCTION
      3. DOING THE INTELLIGENCE WORK
      4. DISCUSSION AND CONCLUSION
    3. Chapter 3: Champion for Business Intelligence
      1. ABSTRACT
      2. INTRODUCTION
      3. RESEARCH SECTION: GATHERING REQUIREMENTS AND CALCULATING BENEFITS
      4. USER AND FUNCTIONAL REQUIREMENTS ARE NOT SPECIFIC TO A BUSINESS PROBLEM
      5. CALCULATING BENEFITS
      6. FINANCIAL MEASURES
      7. BENEFITS REALIZATION CATEGORIES
      8. CASE STUDIES
      9. CASE STUDY 1: HARRAH’S ENTERTAINMENT (NUCLEUS RESEARCH, INC., 2004)
      10. CASE STUDY 2: MARTIN’S POINT HEALTH CARE (NUCLEUS RESEARCH, INC., 2009)
      11. CASE STUDY 3: US COAST GUARD (NUCLEUS RESEARCH INC., 2005)
      12. ANALYSIS SECTION
      13. SMART BUSINESS GOALS
      14. THREE STEP TOOLKIT FOR BI REQUIREMENTS GATHERING
      15. USER INTERVIEWS
      16. INTERACTIVE REPORTS
      17. CONCLUSION
    4. Chapter 4: Enterprise Intelligence
      1. ABSTRACT
      2. INTRODUCTION
      3. CASE STUDY METHODOLOGY
      4. CASE STUDY RESULTS AND COMMENTARY
      5. DATA
      6. ARCHITECTURE
      7. KEY OBSERVATIONS FROM THE CASE STUDY
      8. ENTERPRISE INTELLIGENCE AND THE FUTURE OF BUSINESS INTELLIGENCE
      9. CONCLUSIONS AND FUTURE RESEARCH
      10. APPENDIX
    5. Chapter 5: Business Intelligence Competency Centers
      1. ABSTRACT
      2. INTRODUCTION
      3. CASE STUDY 1: MASSHOUSING (COGNOS, 2008) AND (MACMILLAN, 2008)
      4. CASE STUDY 2: MARTIN’S POINT HEALTH CARE (NUCLEUS RESEARCH, 2009)
    6. Chapter 6: BI’s Impact on Analyses and Decision Making Depends on the Development of Less Complex Applications
      1. ABSTRACT
      2. INTRODUCTION
      3. RESEARCH
      4. WHY IS BI UNNECESSARILY COMPLEX FOR THE COMMON USER?
      5. ANALYSIS
      6. BI AND THE END-USER
      7. CONCLUSION AND RECOMMENDATIONS
    7. Chapter 7: Discovering Business Intelligence from the Subjective Web Data
      1. ABSTRACT
      2. 1. INTRODUCTION
      3. 2. THE UNDERPINNINGS OF OPINION MINING
      4. 3. WEB OPINION MINING CLASSIFICATION
      5. 4. BUSINESS IMPLICATIONS OF OPINION MINING
      6. 5. IMPLICATIONS FOR RESEARCH AND PRACTICE
      7. 6. FUTURE RESEARCH DIRECTIONS
      8. 7. CONCLUSION
    8. Chapter 8: Business Intelligence Enhances Strategic, Long-Range Planning in the Commercial Aerospace Industry
      1. ABSTRACT
      2. INTRODUCTION
      3. 1. RESEARCH
      4. 2. ANALYSIS
      5. 3. SUMMARY
    9. Chapter 9: Performance Management through Societal Performance Indicators
      1. ABSTRACT
      2. INTRODUCTION
      3. RESEARCH
      4. ANALYSIS
      5. RESULTS
    10. Chapter 10: Business Intelligence Should be Centralized
      1. ABSTRACT
      2. INTRODUCTION
      3. RESEARCH
      4. ANALYSIS
      5. CONCLUSION
    11. Chapter 11: The Future Talent Shortage Will Force Global Companies to use HR Analytics to Help Manage and Predict Future Human Capital Needs
      1. ABSTRACT
      2. INTRODUCTION
      3. CONCLUSION
  7. Section 2: Analytic Issues
    1. Chapter 12: Intelligent Analytics
      1. ABSTRACT
      2. INTRODUCTION
      3. WEB ANALYTICS: AN OVERVIEW
      4. TRADITIONAL BI: A SILO VIEW
      5. INTELLIGENT ANALYTICS: TRENDS AND CAPABILITIES
      6. SUMMARY
    2. Chapter 13: Strategies for Improving the Efficacy of Fusion Question Answering Systems
      1. ABSTRACT
      2. INTRODUCTION
      3. QA ALGORITHMS
      4. EXPERIMENT
      5. RESULTS
      6. IMPLICATIONS
      7. CONCLUSION AND FUTURE WORK
  8. Section 3: Technology Issues
    1. Chapter 14: Test-Driven Development of Data Warehouses
      1. ABSTRACT
      2. INTRODUCTION
      3. STATUS OF TDD IN THE BI AND DATA WAREHOUSING SPACE
      4. BACKGROUND: WHAT IS TEST-DRIVEN DEVELOPMENT?
      5. TDD FOR A SOFTWARE PROJECT
      6. THE “RIGHT” LEVEL OF TESTING
      7. BUSINESS ENVIRONMENT CHALLENGES
      8. FAILING TO MEET THE USER’S NEEDS
      9. APPLYING TDD TO A DW PROJECT
      10. ADDRESSING DATA QUALITY
      11. TEST CASES ENSURE SYSTEM ROBUSTNESS
      12. CONCLUSION
    2. Chapter 15: Uncovering Actionable Knowledge in Corporate Data with Qualified Association Rules
      1. ABSTRACT
      2. 1. INTRODUCTION
      3. 2. MARKET BASKET ANALYSIS AND QUALIFIED ASSOCIATION RULES - OVERVIEW
      4. 3. APPLICATION OF QUALIFIED ASSOCIATION RULE DATA MINING METHOD ON A CORPORATE DATASET
      5. 4. STANDARD ASSOCIATION RULES VS. QUALIFIED ASSOCIATION RULES COMPARISON
      6. 5. TECHNICAL AND IMPLEMENTATION ISSUES OF THE WORKING SYSTEM
      7. 6. CONCLUSION
    3. Chapter 16: 10 Principles to Ensure Your Data Warehouse Implementation is a Failure
      1. ABSTRACT
      2. INTRODUCTION
      3. DATA WAREHOUSE IMPLEMENTATION FAILURE
      4. STRATEGY AND DESIGN
      5. IMPLEMENTATION MANAGEMENT AND COMMUNICATION
      6. TECHNOLOGY AND RESOURCE INVESTMENT
      7. CONCLUSION
    4. Chapter 17: Business Intelligence Conceptual Model
      1. ABSTRACT
      2. 1. INTRODUCTION
      3. 2. RELEVANT LITERATURE
      4. 3. RESEARCH METHODOLOGY
      5. 4. BISCOM DEVELOPMENT
      6. 5. EVALUATION OF BISCOM
      7. 6. RESEARCH CONTRIBUTIONS
      8. 7. CONCLUSION AND FUTURE WORK
    5. Chapter 18: Mitigating Risk
      1. ABSTRACT
      2. INTRODUCTION
      3. SECURITY TECHNOLOGY - PAST 10 YEARS
      4. MANAGING RISK AND THE CURRENT THREAT LANDSCAPE
      5. SECURITY INFORMATION AND EVENT MANAGEMENT - SIEM
      6. THE FUTURE OF SIEM
      7. CONCLUSION – THE BOTTOM LINE
    6. Chapter 19: IT and Business Can Succeed in BI by Embracing Agile Methodologies
      1. ABSTRACT
      2. INTRODUCTION
      3. RESEARCH QUESTIONS
      4. TIMELINE LEADING UP TO AGILE METHODOLOGIES
      5. RECOMMENDATION – AGILE DATA WAREHOUSING (ADW)
    7. Chapter 20: Agile Development in Data Warehousing
      1. ABSTRACT
      2. 1. INTRODUCTION
      3. 2. LITERATURE RESEARCH
      4. 3. WATERFALL VS. AGILE DEVELOPMENT METHODOLOGIES
      5. 4. FITTING AGILE DEVELOPMENT METHODOLOGY IN DATA WAREHOUSING
      6. 5. CONCLUSION
  9. Compilation of References
  10. About the Contributors