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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 informati… Read more
LIMITED OFFER
Immediately download your ebook while waiting for your print delivery. No promo code needed.
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.
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
DM