Executing Data Quality Projects: Ten Steps to Quality Data and Trusted Information (TM)

Executing Data Quality Projects 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.

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 that is available online.

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 Steps™ 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
6. 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 Steps™ Overview
Definitions of Data Categories