Data quality the accuracy dimension
Data Quality: The Accuracy Dimension is about assessing the quality of corporate data and improving its accuracy using the data profiling method. Corporate data is increasingly important as companies continue to find new ways to use it. Likewise, improving the accuracy of data in information systems...
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| Format: | eBook |
| Language: | Inglés |
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San Francisco :
Morgan Kaufmann
c2003.
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| Series: | The Morgan Kaufmann Series in Data Management Systems
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| Subjects: | |
| See on Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009627726806719 |
Table of Contents:
- Front Cover; Data Quality: The Accuracy Dimension; Copyright Page; Contents; Foreword; Preface; Part I: Understanding Data Accuracy; Chapter 1. The Data Quality Problem; 1.1 Data Is a Precious Resource; 1.2 Impact of Continuous Evolution of Information Systems; 1.3 Acceptance of Inaccurate Data; 1.4 The Blame for Poor-Quality Data; 1.5 Awareness Levels; 1.6 Impact of poor-Quality Data; 1.7 Requirements for Making Improvements; 1.8 Expected Value Returned for Quality program; 1.9 Data Quality Assurance Technology; 1.10 Closing Remarks; Chapter 2. Definition of Accurate Data
- 2.1 Data Quality Definitions2.2 Principle of Unintended Uses; 2.3 Data Accuracy Defined; 2.4 Distribution of Inaccurate Data; 2.5 Can Total Accuracy Be Achieved?; 2.6 Finding Inaccurate Values; 2.7 How Important Is It to Get Close?; 2.8 Closing Remarks; Chapter 3. Sources of Inaccurate Data; 3.1 Initial Data Entry; 3.2 Data Accuracy Decay; 3.3 Moving and Restructuring Data; 3.4 Using Data; 3.5 Scope of Problems; 3.6 Closing Remarks; Part II: Implementing a Data Quality Assurance Program; Chapter 4. Data Quality Assurance; 4.1 Goals of a Data Quality Assurance Program
- 4.2 Structure of a Data Quality Assurance Program4.3 Closing Remarks; Chapter 5. Data Quality Issues Management; 5.1 Turning Facts into Issues; 5.2 Assessing Impact; 5.3 Investigating Causes; 5.4 Developing Remedies; 5.5 Implementing Remedies; 5.6 Post-implementation Monitoring; 5.7 Closing Remarks; Chapter 6. The Business Case for Accurate Data; 6.1 The Value of Accurate Data; 6.2 Costs Associated with Achieving Accurate Data; 6.3 Building the Business Case; 6.4 Closing Remarks; Part III: Data Profiling Technology; Chapter 7. Data Profiling Overview; 7.1 Goals of Data Profiling
- 7.2 General Model7.3 Data Profiling Methodology; 7.4 Analytical Methods Used in Data Profiling; 7.5 When Should Data Profiling Be Done?; 7.6 Closing Remarks; Chapter 8. Column Property Analysis; 8.1 Definitions; 8.2 The Process for Profiling Columns; 8.3 Profiling Properties for Columns; 8.4 Mapping with Other Columns; 8.5 Value-Level Remedies; 8.6 Closing Remarks; Chapter 9. Structure Analysis; 9.1 Definitions; 9.2 Understanding the Structures Being Profiled; 9.3 The Process for Structure Analysis; 9.4 The Rules for Structure; 9.5 Mapping with Other Structures; 9.6 Structure-Level Remedies
- 9.7 Closing RemarksChapter 10. Simple Data Rule Analysis; 10.1 Definitions; 10.2 The Process for Analyzing Simple Data Rules; 10.3 Profiling Rules for Single Business Objects; 10.4 Mapping with Other Applications; 10.5 Simple Data Rule Remedies; 10.6 Closing Remarks; Chapter 11.Complex Data Rule Analysis; 11.1 Definitions; 11.2 The Process for Profiling Complex Data Rules; 11.3 Profiling Complex Data Rules; 11.4 Mapping with Other Applications; 11.5 Multiple-Object Data Rule Remedies; 11.6 Closing Remarks; Chapter 12. Value Rule Analysis; 12.1 Definitions; 12.2 Process for Value Rule Analysis
- 12.3 Types of Value Rules
