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Executing Data Quality Projects
Ten Steps to Quality Data and Trusted Information (TM)
- 1st Edition - July 11, 2008
- Author: Danette McGilvray
- Language: English
- Paperback ISBN:9 7 8 - 0 - 1 2 - 3 7 4 3 6 9 - 5
- eBook ISBN:9 7 8 - 0 - 0 8 - 0 9 5 1 5 8 - 4
- eBook ISBN:9 7 8 - 0 - 0 8 - 0 5 5 8 3 9 - 4
Executing Data Quality Projects: Ten Steps to Quality Data and Trusted Information (TM) presents a systematic, proven approach to improving and creating data and informati… Read more
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Request a sales quoteExecuting 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.
- 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
IntroductionThe Reason for This Book Intended Audiences Structure of This Book How to Use This Book Acknowledgements
Chapter 1. OverviewImpact of Information and Data Quality About the Methodology Approaches to Data Quality in Projects Engaging Management
Chapter 2. Key ConceptsIntroductionFramework for Information Quality (FIQ) Information Life Cycle Data Quality Dimensions Business Impact Techniques Data CategoriesData SpecificationsData Governance and Stewardship The Information and Data Quality Improvement Cycle The Ten Steps™ ProcessBest Practices and Guidelines
Chapter 3. The Ten Steps1. Define Business Need and Approach 1.1 Prioritize the Business Issue1.2 Plan the Project
2. Analyze Information Environment2.1 Understand Relevant Requirements2.2 Understand Relevant Data and Specifications2.3 Understand Relevant Technology2.4 Understand Relevant Processes2.5 Understand Relevant People/Organizations2.6 Define the Information Life Cycle2.7 Design Data Capture and Assessment Plan 3. Assess Data Quality3.1 Data Specifications3.2 Data Integrity Fundamentals3.3 Duplication3.4 Accuracy3.5 Consistency and Synchronization3.6 Timeliness and Availability3.7 Ease of Use and Maintainability3.8 Data Coverage3.9 Presentation Quality3.10 Perception, Relevance, and Trust3.11 Data Decay3.12 Transactability 4. Assess Business Impact 4.1 Anecdotes4.2 Usage4.3 Five “Whys”4.4 Benefit vs. Cost Matrix4.5 Ranking and Prioritization4.6 Process Impact4.7 Cost of Low Quality Data4.8 Cost-Benefit Analysis 5. Identify Root Causes 5.1 Five “Whys” for Root Cause5.2 Track and Trace5.3 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 ProjectProjects and The Ten StepsData Quality Project RolesProject Timing
Chapter 5. Other Techniques and ToolsIntroductionInformation Life Cycle ApproachesCapture Data Analyze and Document Results Metrics Data Quality Tools The Ten Steps and Six Sigma
Chapter 6. A Few Final Words
Appendix. Quick ReferencesFramework 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
- No. of pages: 352
- Language: English
- Edition: 1
- Published: July 11, 2008
- Imprint: Morgan Kaufmann
- Paperback ISBN: 9780123743695
- eBook ISBN: 9780080951584
- eBook ISBN: 9780080558394
DM
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 [email protected]. 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, USARead Executing Data Quality Projects on ScienceDirect