Executing data quality projects : ten steps to quality data and trusted information /

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: McGilvray, Danette (Autor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: London, United Kingdom ; San Diego, CA, United States : Academic Press, [2021]
Edición:Second edition.
Temas:
Information technology > Management.
Electronic data processing > Quality control.
Technologie de l'information > Gestion.
Electronic data processing > Quality control
Information technology > Management
Acceso en línea:Texto completo
Tabla de Contenidos:
  • Intro
  • Executing Data Quality Projects: Ten Steps to Quality Data and Trusted Information (TM)
  • Copyright
  • In Praise Of
  • Dedication
  • Contents
  • Acknowledgments
  • Foreword
  • Introduction
  • The Reason for This Book
  • What Is in This Book
  • Intended Audiences and How to Use This Book
  • Why a Second Edition
  • My Goals for You
  • Get Started!
  • Structure of This Book
  • Chapter 1 Data Quality and the Data-Dependent World
  • Data, Data Everywhere
  • Trends and the Need for High-Quality Data
  • Data and Information
  • Assets to Be Managed
  • The Leader's Data Manifesto
  • What You Can Do
  • Are You Ready to Change?
  • Chapter 2 Data Quality in Action
  • Introduction to Chapter 2
  • A Word About Tools
  • Real Issues Need Real Solutions
  • About the Ten Steps Methodology
  • The Data in Action Triangle
  • Preparing Your People
  • Engaging Management
  • Key Terms
  • Chapter 2 Summary
  • Chapter 3 Key Concepts
  • Introduction to Chapter 3
  • The Framework for Information Quality
  • The Information Life Cycle
  • Data Quality Dimensions
  • Business Impact Techniques
  • Data Categories
  • Data Specifications
  • Data Governance and Stewardship
  • Ten Steps Process Overview
  • Data Quality Improvement Cycle
  • Concepts and Action
  • Making the Connection
  • Chapter 3 Summary
  • Chapter 4 The Ten Steps Process
  • Introduction to Chapter 4
  • Step 1 Determine Business Needs and Approach
  • Introduction to Step 1
  • Step 1.1 Prioritize Business Needs and Select Project Focus
  • Business Benefit and Context
  • Approach
  • Sample Output and Templates
  • Step 1.2 Plan the Project
  • Business Benefit and Context
  • Approach
  • Sample Output and Templates
  • Step 1 Summary
  • Step 2 Analyze Information Environment
  • Introduction to Step 2
  • Step 2.1 Understand Relevant Requirements and Constraints
  • Business Benefit and Context
  • Approach.
  • Sample Output and Templates
  • Step 2.2 Understand Relevant Data and Data Specifications
  • Business Benefit and Context
  • Approach
  • Sample Output and Templates
  • Step 2.3 Understand Relevant Technology
  • Business Benefit and Context
  • Approach
  • Sample Output and Templates
  • Step 2.4 Understand Relevant Processes
  • Business Benefit and Context
  • Approach
  • Sample Output and Templates
  • Step 2.5 Understand Relevant People and Organizations
  • Business Benefit and Context
  • Approach
  • Sample Output and Templates
  • Step 2.6 Understand Relevant Information Life Cycle
  • Business Benefit and Context
  • Approach
  • Sample Output and Templates
  • Step 2 Summary
  • Step 3 Assess Data Quality
  • Introduction to Step 3
  • Step 3.1 Perception of Relevance and Trust
  • Business Benefit and Context
  • Approach
  • Sample Output and Templates
  • Step 3.2 Data Specifications
  • Business Benefit and Context
  • Approach
  • Sample Output and Templates
  • Step 3.3 Data Integrity Fundamentals
  • Business Benefit and Context
  • Approach
  • Sample Output and Templates
  • Step 3.4 Accuracy
  • Business Benefit and Context
  • Approach
  • Sample Output and Templates
  • Step 3.5 Uniqueness and Deduplication
  • Business Benefit and Context
  • Approach
  • Sample Output and Templates
  • Step 3.6 Consistency and Synchronization
  • Business Benefit and Context
  • Approach
  • Sample Output and Templates
  • Step 3.7 Timeliness
  • Business Benefit and Context
  • Approach
  • Sample Output and Templates
  • Step 3.8 Access
  • Business Benefit and Context
  • Approach
  • Sample Output and Templates
  • Step 3.9 Security and Privacy
  • Business Benefit and Context
  • Approach
  • Sample Output and Templates
  • Step 3.10 Presentation Quality
  • Business Benefit and Context
  • Approach
  • Sample Output and Templates
  • Step 3.11 Data Coverage
  • Business Benefit and Context.
  • Approach
  • Sample Output and Templates
  • Step 3.12 Data Decay
  • Business Benefit and Context
  • Approach
  • Sample Output and Templates
  • Step 3.13 Usability and Transactability
  • Business Benefit and Context
  • Approach
  • Sample Output and Templates
  • Step 3.14 Other Relevant Data Quality Dimensions
  • Business Benefit and Context
  • Approach
  • Sample Output and Templates
  • Step 3 Summary
  • Step 4 Assess Business Impact
  • Introduction to Step 4
  • Step 4.1 Anecdotes
  • Business Benefit and Context
  • Approach
  • Sample Output and Templates
  • Step 4.2 Connect the Dots
  • Business Benefit and Context
  • Approach
  • Sample Output and Templates
  • Step 4.3 Usage
  • Business Benefit and Context
  • Approach
  • Sample Output and Templates
  • Step 4.4 Five Whys for Business Impact
  • Business Benefit and Context
  • Approach
  • Sample Output and Templates
  • Step 4.5 Process Impact
  • Business Benefit and Context
  • Approach
  • Sample Output and Templates
  • Step 4.6 Risk Analysis
  • Business Benefit and Context
  • Approach
  • Sample Output and Templates
  • Step 4.7 Perception of Relevance and Trust
  • Business Benefit and Context
  • Approach
  • Sample Output and Templates
  • Step 4.8 Benefit vs. Cost Matrix
  • Business Benefit and Context
  • Approach
  • Sample Output and Templates
  • Step 4.9 Ranking and Prioritization
  • Business Benefit and Context
  • Approach
  • Sample Output and Templates
  • Step 4.10 Cost of Low-Quality Data
  • Business Benefit and Context
  • Approach
  • Sample Output and Templates
  • Step 4.11 Cost-Benefit Analysis and ROI
  • Business Benefit and Context
  • Approach
  • Sample Output and Templates
  • Step 4.12 Other Relevant Business Impact Techniques
  • Business Benefit and Context
  • Approach
  • Sample Output and Templates
  • Step 4 Summary
  • Step 5 Identify Root Causes
  • Introduction to Step 5.
  • Step 5.1 Five Whys for Root Causes
  • Business Benefit and Context
  • Approach
  • Sample Output and Templates
  • Step 5.2 Track and Trace
  • Business Benefit and Context
  • Approach
  • Sample Output and Templates
  • Step 5.3 Cause-and-Effect/Fishbone Diagram
  • Business Benefit and Context
  • Approach
  • Sample Output and Templates
  • Step 5.4 Other Relevant Root Cause Analysis Techniques
  • Business Benefit and Context
  • Step 5 Summary
  • Step 6 Develop Improvement Plans
  • Business Benefit and Context
  • Approach
  • Sample Output and Templates
  • Step 6 Summary
  • Step 7 Prevent Future Data Errors
  • Business Benefit and Context
  • Approach
  • Sample Output and Templates
  • Step 7 Summary
  • Step 8 Correct Current Data Errors
  • Business Benefit and Context
  • Approach
  • Sample Output and Templates
  • Step 8 Summary
  • Step 9 Monitor Controls
  • Business Benefit and Context
  • Approach
  • Sample Output and Templates
  • Step 9 Summary
  • Step 10 Communicate, Manage, and Engage People Throughout
  • Business Benefit and Context
  • Approach
  • Sample Output and Templates
  • Step 10 Summary
  • Chapter 4 Summary
  • Chapter 5 Structuring Your Project
  • Introduction to Chapter 5
  • Types of Data Quality Projects
  • Project Objectives
  • Comparing SDLCs
  • Data Quality and Governance in SDLCs
  • Roles in Data Quality Projects
  • Project Timing, Communication, and Engagement
  • Chapter 5 Summary
  • Chapter 6 Other Techniques and Tools
  • Introduction to Chapter 6
  • Track Issues and Action Items
  • Design Data Capture and Assessment Plans
  • Analyze, Synthesize, Recommend, Document, and Act on Results
  • Information Life Cycle Approaches
  • Conduct a Survey
  • Metrics
  • The Ten Steps and Other Methodologies and Standards
  • Tools for Managing Data Quality
  • Chapter 6 Summary
  • Chapter 7 A Few Final Words
  • Appendix: Quick References.
  • Framework for Information Quality
  • POSMAD Interaction Matrix Detail
  • Data Quality Dimensions
  • Business Impact Techniques
  • The Ten Steps Process
  • Process Flows for Steps 1-4
  • Data in Action Triangle
  • Glossary
  • List of Figures, Tables, and Templates
  • Bibliography
  • Index
  • About the Author.

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