Information is currency. In today’s world of instant global communication and rapidly changing trends, up-to-date and reliable information is essential to effective competition. 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 Executing Data Quality Projects: Ten Steps to Quality Data and Trusted Information, Danette McGilvray presents a systematic, proven approach to improving and creating data and information quality within the enterprise. She describes a methodology that combines a conceptual framework for understanding information quality with the tools, techniques, and instructions for improving and creating information quality. Her trademarked "Ten Steps" approach 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 that is available online.
Database analysts, data analysts, data administrators, data architects, enterprise architects, data warehouse engineers, business analysts, developers, DBAs, subject matter experts, data modelers, and data stewards and their managers.
The Reason for This Book
Structure of This Book
How to Use This Book
Chapter 1. Overview
Impact of Information and Data Quality
About the Methodology
Approaches to Data Quality in Projects
Chapter 2. Key Concepts
Framework for Information Quality (FIQ)
Information Life Cycle
Data Quality Dimensions
Business Impact Techniques
Data Governance and Stewardship
The Information and Data Quality Improvement Cycle
The Ten Steps™ Process
Best Practices and Guidelines
Chapter 3. The Ten Steps
- Define Business Need and Approach
1.1 Prioritize the Business Issue
1.2 Plan the Project
- Analyze Information Environment
2.1 Understand Relevant Requirements
2.2 Understand Relevant Data and Specifications
2.3 Understand Relevant Technology
2.4 Understand Relevant Processes
2.5 Understand Relevant People/Organizations
2.6 Define the Information Life Cycle
2.7 Design Data Capture and Assessment Plan
- Assess Data Quality
3.1 Data Specifications
3.2 Data Integrity Fundamentals
- No. of pages:
- © Morgan Kaufmann 2008
- 11th July 2008
- Morgan Kaufmann
- eBook ISBN:
- eBook ISBN:
- Paperback ISBN:
My esteemed colleague describes a practical approach for planning and managing information quality. I recommend you read, understand, and apply the learnings found here.
- Larry P. English, President and Principal, Information Impact International, creator of the TIQM Quality System. Conceiver and co-Founder of the International Association for Information and Data Quality
In a subject that is long on talk and short on practical advice for implementation, Danette McGilvray is a refreshing exception. If you want to know HOW to execute data quality projects, read this book -- everything you need to know is in here.
- David Plotkin, Data Quality Manager, California State Automobile Association
This book is a gem. Tested, validated and polished over a distinguished career as a practitioner and consultant, Danette's Ten Steps methodology shines as a unique and much needed contribution to the information quality discipline. This practical and insightful book will quickly become the reference of choice for all those leading or participating in information quality improvement projects. Experienced project managers will use it to update and deepen their knowledge, new ones will use it as a roadmap to quickly become effective. Managers in organizations that have embraced generic improvement methodologies such as six sigma, lean or have developed internal ones would be wise to hand this book to their Black Belts and other improvement leaders.
- C. Lwanga Yonke, Information Quality Practitioner.
Danette’s book takes a pragmatic and practical approach to achieving the desired state of data quality within an organization. It is a "must-read" for any organization starting out on the road to data quality.
– Susan Stewart Goubeaux, Director, Business Intelligence, FHLBanks Office of Finance