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Tables of Contents for Data Quality
Chapter/Section Title
Page #
Page Count
Foreword
vii
Preface
xv
PART I Understanding Data Accuracy
1
64
The Data Quality Problem
3
21
Data Is a Precious Resource
3
2
Impact of Continuous Evolution of Information Systems
5
3
Acceptance of Inaccurate Data
8
1
The Blame for Poor-Quality Data
9
1
Awareness Levels
10
2
Impact of Poor-Quality Data
12
2
Requirements for Making Improvements
14
1
Expected Value Returned for Quality Program
15
1
Data Quality Assurance Technology
16
6
Closing Remarks
22
2
Definition of Accurate Data
24
19
Data Quality Definitions
24
3
Principle of Unintended Uses
27
2
Data Accuracy Defined
29
3
Distribution of Inaccurate Data
32
2
Can Total Accuracy Be Achieved?
34
1
Finding Inaccurate Values
35
5
How Important Is It to Get Close?
40
1
Closing Remarks
41
2
Sources of Inaccurate Data
43
22
Initial Data Entry
44
6
Data Accuracy Decay
50
2
Moving and Restructuring Data
52
10
Using Data
62
1
Scope of Problems
63
1
Closing Remarks
64
1
PART II Implementing a Data Quality Assurance Program
65
54
Data Quality Assurance
67
13
Goals of a Data Quality Assurance Program
68
1
Structure of a Data Quality Assurance Program
69
9
Closing Remarks
78
2
Data Quality Issues Management
80
23
Turning Facts into Issues
81
4
Assessing Impact
85
2
Investigating Causes
87
7
Developing Remedies
94
5
Implementing Remedies
99
1
Post-implementation Monitoring
99
2
Closing Remarks
101
2
The Business Case for Accurate Data
103
16
The Value of Accurate Data
103
5
Costs Associated with Achieving Accurate Data
108
1
Building the Business Case
108
10
Closing Remarks
118
1
PART III Data Profiling Technology
119
141
Data Profiling Overview
121
22
Goals of Data Profiling
122
1
General Model
123
7
Data Profiling Methodology
130
6
Analytical Methods Used in Data Profiling
136
4
When Should Data Profiling Be Done?
140
1
Closing Remarks
141
2
Column Property Analysis
143
30
Definitions
143
9
The Process for Profiling Columns
152
3
Profiling Properties for Columns
155
12
Mapping with Other Columns
167
2
Value-Level Remedies
169
2
Closing Remarks
171
2
Structure Analysis
173
42
Definitions
173
14
Understanding the Structures Being Profiled
187
1
The Process for Structure Analysis
188
5
The Rules for Structure
193
17
Mapping with Other Structures
210
2
Structure-Level Remedies
212
1
Closing Remarks
213
2
Simple Data Rule Analysis
215
22
Definitions
216
4
The Process for Analyzing Simple Data Rules
220
5
Profiling Rules for Single Business Objects
225
5
Mapping with Other Applications
230
2
Simple Data Rule Remedies
232
3
Closing Remarks
235
2
Complex Data Rule Analysis
237
9
Definitions
237
1
The Process for Profiling Complex Data Rules
238
2
Profiling Complex Data Rules
240
4
Mapping with Other Applications
244
1
Multiple-Object Data Rule Remedies
245
1
Closing Remarks
245
1
Value Rule Analysis
246
9
Definitions
246
1
Process for Value Rule Analysis
247
2
Types of Value Rules
249
3
Remedies for Value Rule Violations
252
1
Closing Remarks
253
2
Summary
255
5
Data Quality Is a Major Issue for Corporations
255
1
Moving to a Position of High Data Quality Requires an Explicit Effort
256
1
Data Accuracy Is the Cornerstone for Data Quality Assurance
257
3
APPENDIX A Examples of Column Properties, Data Structure, Data Rules, and Value Rules
260
12
A.1 Business Objects
260
1
A.2 Tables
260
3
A.3 Column Properties
263
3
A.4 Structure Rules
266
3
A.5 Simple Data Rules
269
1
A.6 Complex Data Rules
270
1
A.7 Value Rules
271
1
APPENDIX B Content of a Data Profiling Repository
272
7
B.1 Schema Definition
272
1
B.2 Business Objects
272
1
B.3 Domains
273
1
B.4 Data Source
273
1
B.5 Table Definitions
274
2
B.6 Synonyms
276
1
B.7 Data Rules
277
1
B.8 Value Rules
277
1
B.9 Issues
278
1
References
279
4
Books on Data Quality Issues
279
1
Books on Data Quality Technologies
279
2
Articles
281
2
Index
283
11
About the Author
294