Executing Data Quality Projects

Executing Data Quality Projects

by Danette McGilvray
Released September 2008
Publisher(s): Morgan Kaufmann
ISBN: 9780080558394

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Book description

Information is currency. Recent studies show that data quality problems are costing businesses billions of dollars each year, with poor data linked to waste and inefficiency, damaged credibility among customers and suppliers, and an organizational inability to make sound decisions. In this important and timely new book, Danette McGilvray presents her “Ten Steps” approach to information quality, a proven method for both understanding and creating information quality in the enterprise. Her trademarked approach—in which she has trained Fortune 500 clients and hundreds of workshop attendees—applies to all types of data and to all types of organizations.

* Includes numerous templates, detailed examples, and practical advice for executing every step of the “Ten Steps” approach.* Allows for quick reference with an easy-to-use format highlighting key concepts and definitions, important checkpoints, communication activities, and best practices.* A companion Web site includes links to numerous data quality resources, including many of the planning and information-gathering templates featured in the text, quick summaries of key ideas from the Ten Step methodology, and other tools and information available online.

Table of contents

  1. Cover
  2. In Praise of Executing Data Quality Projects
  3. Title Page
  4. Copyright
  5. Dedication
  6. ACKNOWLEDGMENTS
  7. INTRODUCTION
    1. The Reason for This Book
    2. Intended Audiences
    3. Structure of This Book
    4. How to Use This Book
  8. CHAPTER 1 Overview
    1. The Impact of Information and Data Quality
    2. About the Methodology: Concepts and Steps
    3. Approaches to Data Quality in Projects
    4. Engaging Management
  9. CHAPTER 2 Key Concepts
    1. Introduction
    2. The Framework for Information Quality
    3. The Information Life Cycle
    4. Data Quality Dimensions
    5. Business Impact Techniques
    6. Data Categories
    7. Data Specifi cations
    8. Data Governance and Data Stewardship
    9. The Information and Data Quality Improvement Cycle
    10. The Ten Steps Process
    11. Best Practices and Guidelines
  10. CHAPTER 3 The Ten Steps Process
    1. Introduction
    2. Step 1 Define Business Need and Approach
      1. Introduction
      2. Step 1.1 Prioritize the Business Issue
      3. Step 1.2 Plan the Project
    3. Step 2 Analyze Information Environment
      1. Introduction
      2. Step 2.1 Understand Relevant Requirements
      3. Step 2.2 Understand Relevant Data and Specifications
      4. Step 2.3 Understand Relevant Technology
      5. Step 2.4 Understand Relevant Processes
      6. Step 2.5 Understand Relevant People/Organizations
      7. Step 2.6 Define the Information Life Cycle
      8. Step 2.7 Design Data Capture and Assessment Plan
    4. Step 3 Assess Data Quality
      1. Introduction
      2. Step 3.1 Data Specifications
      3. Step 3.2 Data Integrity Fundamentals
      4. Step 3.3 Duplication
      5. Step 3.4 Accuracy
      6. Step 3.5 Consistency and Synchronization
      7. Step 3.6 Timeliness and Availability
      8. Step 3.7 Ease of Use and Maintainability
      9. Step 3.8 Data Coverage
      10. Step 3.9 Presentation Quality
      11. Step 3.10 Perception, Relevance, and Trust
      12. Step 3.11 Data Decay
      13. Step 3.12 Transactability
    5. Step 4 Assess Business Impact
      1. Introduction
      2. Step 4.1 Anecdotes
      3. Step 4.2 Usage
      4. Step 4.3 Five “Whys” for Business Impact
      5. Step 4.4 Benefit versus Cost Matrix
      6. Step 4.5 Ranking and Prioritization
      7. Step 4.6 Process Impact
      8. Step 4.7 Cost of Low-Quality Data
      9. Step 4.8 Cost-Benefit Analysis
    6. Step 5 Identify Root Causes
      1. Introduction
      2. Step 5.1 Five “Whys” for Root Cause
      3. Step 5.2 Track and Trace
      4. Step 5.3 Cause-and-Effect/Fishbone Diagram
    7. Step 6 Develop Improvement Plans
    8. Step 7 Prevent Future Data Errors
    9. Step 8 Correct Current Data Errors
    10. Step 9 Implement Controls
    11. Step 10 Communicate Actions and Results
    12. The Ten Steps Process Summary
  11. CHAPTER 4 Structuring Your Project
    1. Projects and The Ten Steps
    2. Data Quality Project Roles
    3. Project Timing
  12. CHAPTER 5 Other Techniques and Tools
    1. Introduction
    2. Information Life Cycle Approaches
    3. Capture Data
    4. Analyze and Document Results
    5. Metrics
    6. Data Quality Tools
    7. The Ten Steps and Six Sigma
  13. CHAPTER 6 A Few Final Words
  14. APPENDIX Quick References
    1. The Framework for Information Quality
    2. The POSMAD Interaction Matrix in Detail
    3. POSMAD Phases and Activities
    4. Data Quality Dimensions
    5. Business Impact Techniques
    6. Overview of The Ten Steps Process
    7. Definitions of Data Categories
  15. GLOSSARY
  16. BIBLIOGRAPHY
  17. LIST OF FIGURES, TABLES, AND TEMPLATES
  18. INDEX
  19. ABOUT THE AUTHOR
  20. Instructions for online access

Product information

  • Title: Executing Data Quality Projects
  • Author(s): Danette McGilvray
  • Release date: September 2008
  • Publisher(s): Morgan Kaufmann
  • ISBN: 9780080558394