Data Quality: The Accuracy Dimension (The Morgan Kaufmann Series in Data Management Systems)

ISBN: 1558608915
EAN: 2147483647

Year: 2003
Pages: 133

Authors: Jack E. Olson

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Table of Contents
BackCover
Data Quality-The Accuracy Dimension
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
2.2 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
3.2 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 Program
4.3 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 Model
7.3 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
8.2 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 Remarks
Chapter 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
11.2 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
12.4 Remedies for Value Rule Violations
12.5 Closing Remarks
Chapter 13: Summary
13.2 Moving to a Position of High Data Quality Requires an Explicit Effort
13.3 Data Accuracy Is the Cornerstone for Data Quality Assurance
Appendix A: Examples of Column Properties, Data Structure, Data Rules, and Value Rules
A.2 Tables
A.3 Column Properties
A.4 Structure Rules
A.5 Simple Data Rules
A.6 Complex Data Rules
A.7 Value Rules
Appendix B: Content of a Data Profiling Repository
B.2 Business Objects
B.3 Domains
B.4 Data Source
B.5 Table Definitions
B.6 Synonyms
B.7 Data Rules
B.8 Value Rules
B.9 Issues
References
Books on Data Quality Technologies
Articles
Index
Index_B
Index_C
Index_D
Index_E
Index_F
Index_G-H
Index_I
Index_K-L
Index_M
Index_N
Index_O
Index_P
Index_Q-R
Index_S
Index_T
Index_U
Index_V
Index_W-Z
List of Figures