Executing data quality projects : ten steps to quality data and trusted information
Danette McGilvray
Bok Engelsk 2008 · Electronic books.
| Annen tittel | |
|---|---|
| Utgitt | Amsterdam : Elsevier , c2008
|
| Omfang | 1 online resource (353 p.)
|
| Opplysninger | Description based upon print version of record.. - Front Cover; Executing Data Quality Projects; Copyright Page; Contents; Acknowledgments; Introduction; The Reason for This Book; Intended Audiences; Structure of This Book; How to Use This Book; Chapter 1. Overview; The Impact of Information and Data Quality; About the Methodology: Concepts and Steps; Approaches to Data Quality in Projects; Engaging Management; Chapter 2. Key Concepts; Introduction; The Framework for Information Quality; The Information Life Cycle; Data Quality Dimensions; Business Impact Techniques; Data Categories; Data Specifications; Data Governance and Data Stewardship. - List of Figures, Tables, and Templates. - Projects and The Ten StepsData 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; The Framework for Information Quality; The POSMAD Interaction Matrix in Detail; POSMAD Phases and Activities; Data Quality Dimensions; Business Impact Techniques; Overview of The Ten Steps Process; Definitions of Data Categories; Glossary; Bibliography. - Step 2.6 Define the Information Life CycleStep 2.7 Design Data Capture and Assessment Plan; Step 3 Assess Data Quality; Step 3.1 Data Specifi cations; Step 3.2 Data Integrity Fundamentals; Step 3.3 Duplication; Step 3.4 Accuracy; Step 3.5 Consistency and Synchronization; Step 3.6 Timeliness and Availability; Step 3.7 Ease of Use and Maintainability; Step 3.8 Data Coverage; Step 3.9 Presentation Quality; Step 3.10 Perception, Relevance, and Trust; Step 3.11 Data Decay; Step 3.12 Transactability; Step 4 Assess Business Impact; Step 4.1 Anecdotes; Step 4.2 Usage. - Step 4.3 Five "Whys" for Business ImpactStep 4.4 Benefit versus Cost Matrix; Step 4.5 Ranking and Prioritization; Step 4.6 Process Impact; Step 4.7 Cost of Low-Quality Data; Step 4.8 Cost-Benefit Analysis; Step 5 Identify Root Causes; Step 5.1 Five "Whys" for Root Cause; Step 5.2 Track and Trace; Step 5.3 Cause-and-Effect/Fishbone Diagram; Step 6 Develop Improvement Plans; Step 7 Prevent Future Data Errors; Step 8 Correct Current Data Errors; Step 9 Implement Controls; Step 10 Communicate Actions and Results; The Ten Steps Process Summary; Chapter 4. Structuring Your Project. - The Information and Data Quality Improvement CycleThe Ten Steps Process; Best Practices and Guidelines; Chapter 3. The Ten Steps Process; Introduction; Step 1 Define Business Need and Approach; Introduction; Step 1.1 Prioritize the Business Issue; Step 1.2 Plan the Project; Step 2 Analyze Information Environment; Introduction; Step 2.1 Understand Relevant Requirements; Step 2.2 Understand Relevant Data and Specifi cations; Step 2.3 Understand Relevant Technology; Step 2.4 Understand Relevant Processes; Step 2.5 Understand Relevant People/Organizations. - Information is currency. In today's world of instant global communication and rapidly changing trends, up-to-date and reliable information is essential to effective competition. 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.In Executing Data Quality Projects: Ten Steps to Quality Data and Trusted Information, Danette McGilvray presents a systematic, proven approac
|
| Emner | |
| Sjanger | |
| Dewey | |
| ISBN | 9780123743695
|
