Executing Data Quality Projects: Ten Steps to Quality Data and Trusted Information

Description

Data quality problems cost businesses billions of dollars each year in unnecessary printing, postage, and staffing costs, in the steady erosion of an organization's credibility among customers and suppliers, and the inability to make sound decisions.

Danette McGilvray presents a systematic, proven approach to improving data quality by combining a conceptual framework for understanding information quality with techniques and instructions for improving it. The Ten Step 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.

CONTENTS:

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
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 StepsT Overview
Definitions of Data Categories