Data Quality (eBook)

The Accuracy Dimension

Jack E. Olson (Autor)

eBook Download: PDF

2003 | 1. Auflage
300 Seiten
Elsevier Science (Verlag)
978-0-08-050369-1 (ISBN)

Infos

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 is fast becoming a major goal as companies realize how much it affects their bottom line. Data profiling is a new technology that supports and enhances the accuracy of databases throughout major IT shops. Jack Olson explains data profiling and shows how it fits into the larger picture of data quality.

* Provides an accessible, enjoyable introduction to the subject of data accuracy, peppered with real-world anecdotes.

* Provides a framework for data profiling with a discussion of analytical tools appropriate for assessing data accuracy.

* Is written by one of the original developers of data profiling technology.

* Is a must-read for any data management staff, IT management staff, and CIOs of companies with data assets.

Inhalt

Front Cover 1
Data Quality: The Accuracy Dimension 4
Copyright Page 5
Foreword 8
Contents 10
Preface 16
Part I: Understanding Data Accuracy 20
Chapter 1. The Data Quality Problem 22
1.1 Data Is a Precious Resource 22
1.2 Impact of Continuous Evolution of Information Systems 24
1.3 Acceptance of Inaccurate Data 27
1.4 The Blame for Poor-Quality Data 28
1.5 Awareness Levels 29
1.6 Impact of poor-Quality Data 31
1.7 Requirements for Making Improvements 33
1.8 Expected Value Returned for Quality program 34
1.9 Data Quality Assurance Technology 35
1.10 Closing Remarks 41
Chapter 2. Definition of Accurate Data 43
2.1 Data Quality Definitions 43
2.2 Principle of Unintended Uses 46
2.3 Data Accuracy Defined 48
2.4 Distribution of Inaccurate Data 51
2.5 Can Total Accuracy Be Achieved? 53
2.6 Finding Inaccurate Values 54
2.7 How Important Is It to Get Close? 59
2.8 Closing Remarks 60
Chapter 3. Sources of Inaccurate Data 62
3.1 Initial Data Entry 63
3.2 Data Accuracy Decay 69
3.3 Moving and Restructuring Data 71
3.4 Using Data 81
3.5 Scope of Problems 82
3.6 Closing Remarks 83
Part II: Implementing a Data Quality Assurance Program 84
Chapter 4. Data Quality Assurance 86
4.1 Goals of a Data Quality Assurance Program 87
4.2 Structure of a Data Quality Assurance Program 88
4.3 Closing Remarks 97
Chapter 5. Data Quality Issues Management 99
5.1 Turning Facts into Issues 100
5.2 Assessing Impact 104
5.3 Investigating Causes 106
5.4 Developing Remedies 113
5.5 Implementing Remedies 118
5.6 Post-implementation Monitoring 118
5.7 Closing Remarks 120
Chapter 6. The Business Case for Accurate Data 122
6.1 The Value of Accurate Data 122
6.2 Costs Associated with Achieving Accurate Data 127
6.3 Building the Business Case 127
6.4 Closing Remarks 137
Part III: Data Profiling Technology 138
Chapter 7. Data Profiling Overview 140
7.1 Goals of Data Profiling 141
7.2 General Model 142
7.3 Data Profiling Methodology 149
7.4 Analytical Methods Used in Data Profiling 155
7.5 When Should Data Profiling Be Done? 159
7.6 Closing Remarks 160
Chapter 8. Column Property Analysis 162
8.1 Definitions 162
8.2 The Process for Profiling Columns 171
8.3 Profiling Properties for Columns 174
8.4 Mapping with Other Columns 186
8.5 Value-Level Remedies 188
8.6 Closing Remarks 190
Chapter 9. Structure Analysis 192
9.1 Definitions 192
9.2 Understanding the Structures Being Profiled 206
9.3 The Process for Structure Analysis 207
9.4 The Rules for Structure 212
9.5 Mapping with Other Structures 229
9.6 Structure-Level Remedies 231
9.7 Closing Remarks 232
Chapter 10. Simple Data Rule Analysis 234
10.1 Definitions 235
10.2 The Process for Analyzing Simple Data Rules 239
10.3 Profiling Rules for Single Business Objects 244
10.4 Mapping with Other Applications 249
10.5 Simple Data Rule Remedies 251
10.6 Closing Remarks 254
Chapter 11.Complex Data Rule Analysis 256
11.1 Definitions 256
11.2 The Process for Profiling Complex Data Rules 257
11.3 Profiling Complex Data Rules 259
11.4 Mapping with Other Applications 263
11.5 Multiple-Object Data Rule Remedies 264
11.6 Closing Remarks 264
Chapter 12. Value Rule Analysis 265
12.1 Definitions 265
12.2 Process for Value Rule Analysis 266
12.3 Types of Value Rules 268
12.4 Remedies for Value Rule Violations 271
12.5 Closing Remarks 272
Chapter 13. Summary 274
13.1 Data Quality Is a Major Issue for Corporations 274
13.2 Moving to a Position of High Data Quality Requires an Explicit Effort 275
13.3 Data Accuracy Is the Cornerstone for Data Quality Assurance 276
Appendix A. Examples of Column Properties , Data Structure, Data Rules , and Value Rules 279
A.1 Business Objects 279
A.2 Tables 279
A.3 Column Properties 282
A.4 Structure Rules 285
A.5 Simple Data Rules 288
A.6 Complex Data Rules 289
A.7 Value Rules 290
Appendix B. Content of a Data Profiling Repository 291
B.1 Schema Definition 291
B.2 Business Objects 291
B.3 Domains 292
B.4 Data Source 292
B.5 Table Definitions 293
B.6 Synonyms 295
B.7 Data Rules 296
B.8 Value Rules 296
B.9 Issues 297
References 298
Books on Data Quality Issues 298
Books on Data Quality Technologies 298
Articles 300
Index 302
About the Author 313

Produkt-Details

• Erscheint lt. Verlag: 9.1.2003
• Sprache: englisch
• Themenwelt: Mathematik / Informatik ► Informatik ► Datenbanken
• Themenwelt: Informatik ► Office Programme ► Outlook
• Themenwelt: Mathematik / Informatik ► Informatik ► Software Entwicklung
• Themenwelt: Informatik ► Weitere Themen ► Hardware
• Themenwelt: Sozialwissenschaften ► Kommunikation / Medien ► Buchhandel / Bibliothekswesen
• Themenwelt: Wirtschaft ► Betriebswirtschaft / Management
• ISBN-10: 0-08-050369-1 / 0080503691
• ISBN-13: 978-0-08-050369-1 / 9780080503691