Executing Data Quality Projects
Ten Steps to Quality Data and Trusted Information (TM)
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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.
Key Features
- 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
Readership
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
Table of Contents
Introduction
The Reason for This Book
Intended Audiences
Structure of This Book
How to Use This Book
AcknowledgementsChapter 1. Overview
Impact of Information and Data Quality
About the Methodology
Approaches to Data Quality in Projects
Engaging ManagementChapter 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 GuidelinesChapter 3. The Ten Steps
1. Define Business Need and Approach
1.1 Prioritize the Business Issue
1.2 Plan the Project
2. 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
3. Assess Data Quality
3.1 Data Specifications
3.2 Data Integrity Fundamentals
3.3 Duplication
3.4 Accuracy
3.5 Consistency and Synchronization
3.6 Timeliness and Availability
3.7 Ease of Use and Maintainability
3.8 Data Coverage
3.9 Presentation Quality
3.10 Perception, Relevance, and Trust
3.11 Data Decay
3.12 Transactability
4. Assess Business Impact
4.1 Anecdotes
4.2 Usage
4.3 Five “Whys”
4.4 Benefit vs. Cost Matrix
4.5 Ranking and Prioritization
4.6 Process Impact
4.7 Cost of Low Quality Data
4.8 Cost-Benefit Analysis
5. Identify Root Causes
5.1 Five “Whys” for Root Cause
5.2 Track and Trace
5.3 Cause-and-Effect / Fishbone Diagram
6. Develop Improvement Plans
7. Prevent Future Data Errors
8. Correct Current Data Errors
9. Implement Controls
10. Communicate Actions and ResultsChapter 4. Structuring Your Project
Projects and The Ten Steps
Data Quality Project Roles
Project TimingChapter 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 SigmaChapter 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
Product details
- No. of pages: 352
- Language: English
- Copyright: © Morgan Kaufmann 2008
- Published: July 11, 2008
- Imprint: Morgan Kaufmann
- eBook ISBN: 9780080558394
- Paperback ISBN: 9780123743695
About the Author
Danette McGilvray
Danette McGilvray has devoted more than 25 years to helping people around the world enhance the value of the information assets on which their organizations depend. Focusing on bottom-line results, she helps them manage the quality of their most important data, so the resulting information can be trusted and used with confidence—a necessity in today’s data-dependent world.
Her company, Granite Falls Consulting, excels in bridging the gap between an organization’s strategies, goals, issues, and opportunities and the practical steps necessary to ensure the “right-level” quality of the data and information needed to provide products and services to their customers. They specialize in data quality management to support key business processes, such as analytics, supply chain management, and operational excellence. Communication, change management, and human factors are also emphasized because they affect the trust in and use of data and information.
Granite Falls’ “teach-a-person-how-to-fish” approach helps organizations meet their business objectives while enhancing skills and knowledge that can be used to benefit the organization for years to come. Client needs are met through a combination of consulting, training, one-on-one mentoring, and executive workshops, tailored to fit any situation where data is a component.
Danette first shared her extensive experience in her 2008 book, Executing Data Quality Projects: Ten Steps to Quality Data and Trusted Information™ (Morgan Kaufmann), which has become a classic in the data quality field. Her Ten Steps™ methodology is a structured yet flexible approach to creating, assessing, improving, and sustaining data quality. It can be applied to any type of organization (for profit, government, education, healthcare, non-profit, etc.), and regardless of country, culture, or language. Her book is used as a textbook in university graduate programs. The Chinese translation was the first data quality book available in that language.
The 2021 second edition (Elsevier/Academic Press) updates how-to details, examples, and templates, while keeping the basic Ten Steps, which have held the test of time. With her holistic view of data and information quality, she truly believes that data quality can save the world. She hopes that this edition can help a new generation of data professionals, in addition to inspiring those who already care about or have been responsible for data and information over the years.
You can reach Danette at danette@gfalls.com. Connect with her on LinkedIn and follow her on Twitter at Danette_McG. To see how Granite Falls can help on your journey to quality data and trusted information, and for free downloads of key ideas and tem¬plates from the book, see www.gfalls.com.
Affiliations and Expertise
President and Principle, Granite Falls Consulting, Inc., UT, USA