Executing data quality projects : ten steps to quality data and trusted information

Executing Data Quality Projects: Ten Steps to Quality Data and Trusted Information (TM) presents a systematic, proven approach to improving and creating data and information quality within the enterprise.

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.

This book describes a Ten Step approach that combines a conceptual framework for understanding information quality with the tools, techniques, and instructions for improving and creating information quality. It includes numerous templates, detailed examples, and practical advice for executing every step of the approach. It allows for quick reference with an easy-to-use format highlighting key concepts and definitions, important checkpoints, communication activities, and best practices.

The author's trademarked approach, in which she has trained Fortune 500 clients and hundreds of workshop attendees, applies to all types of data and all types of organizations.

• Introduction
• The Reason for This Book
• Intended Audiences
• Structure of This Book
• How to Use This Book
• Acknowledgements
• Chapter 1 Overview Impact of Information and Data Quality
• About the Methodology
• Approaches to Data Quality in Projects
• Engaging Management
• Chapter 2 Key Concepts Introduction Framework for Information Quality (FIQ)
• Information Life Cycle
• Data Quality Dimensions
• Business Impact Techniques
• Data Categories Data Specifications Data Governance and Stewardship
• The Information and Data Quality Improvement Cycle
• The Ten StepsT Process Best Practices and Guidelines
• Chapter 3 The Ten Steps
• 1 Define Business Need and Approach
• 2 Analyze Information Environment
• 3 Assess Data Quality
• 4 Assess Business Impact
• 5 Identify Root Causes
• Develop Improvement Plans
• 7 Prevent Future Data Errors
• 8 Correct Current Data Errors
• 9 Implement Controls
• 10 Communicate Actions and Results
• Chapter 4 Structuring Your Project
• Projects and The Ten Steps Data Quality
• Project Roles Project Timing
• Chapter 5 Other Techniques and Tools
• Introduction Information Life Cycle Approaches Capture Data
• Analyze and Document Results
• Metrics
• Data Quality Tools
• The Ten Steps and Six Sigma
• Chapter 6 A Few Final Words
• Appendix
• Quick References
• Framework for Information Quality
• Posmad Interaction Matrix Detail
• Posmad Phases and Activities
• Data Quality Dimensions
• Business Impact Techniques
• The Ten StepsT Overview
• Definitions of Data Categories