Managing Data Quality. Tim King
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What is data quality management?14
Summary14
2. CHALLENGES WHEN EXPLOITING AND MANAGING DATA15
The complex data landscape15
Complex decisions16
Virtuous circle or downward spiral?16
Unclear data ownership 17
Backups and data quality17
Data quality and lack of transparency in business cases18
The data triangle 19
Data as a raw material 20
The data machine: expectations vs reality 20
Do your data trust you? 21
The challenge of managing enterprise data quality23
Summary24
3. THE IMPACT OF PEOPLE ON DATA QUALITY25
Comparisons between data quality and health and safety25
People and data 26
The Data Zoo 28
How data behaviours interact 40
Individuals as part of a team 40
Teams within the organisation 41
Data demotivators 42
Summary43
CONTENTS
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CONTENTS
4. CASE STUDIES AND EXAMPLES44
Real-world examples of the impacts of poor data 44
Case study – Mars Climate Orbiter45
Case study – Maintenance productivity targets degrading data quality 46
Case study – Railtrack 47
Case study – Statutory reporting 47
Case study – Oversized trains 48
Case study – Retail fail 48
Case study – Inappropriate controls and haste degradeddata quality 49
Summary49
Part II: A FRAMEWORK FOR DATA QUALITY MANAGEMENT51
5. THE PURPOSE AND SCOPE OF DATA QUALITY MANAGEMENT53
The difference between data management and data quality management 53
Key principles for data quality management 55
Summary56
6. THE ISO 8000-61 APPROACH57
The scope of ISO 8000-6157
The processes in ISO 8000-6157
Summary60
7. DATA QUALITY MANAGEMENT CAPABILITY LEVELS61
Capability Level 161
Capability Level 263
Capability Level 364
Capability Level 466
Capability Level 567
Overall capability model67
Summary68
8. ISO 8000-61 PROCESSES69
Data processing69
Provision of data specifications and work instructions71
Data quality monitoring and control73
Data quality planning74
Data-related support77
Resource provision83
Data quality assurance85
Data quality improvement89
Summary93
9. THE MATURITY JOURNEY94
Planning the journey94
Assessing maturity95
Summary96
CONTENTS
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Part III: IMPLEMENTING DATA QUALITY MANAGEMENT97
10. PREPARING THE ORGANISATION FOR DATA QUALITY MANAGEMENT99
What does a data-enabled organisation look like? 99
Improvement opportunities in typical organisations101
The data quality management journey104
The case for change105
The changing organisation108
The role of the chief data officer109
Preparing the organisation110
Summary111
11. IMPLEMENTING DATA QUALITY MANAGEMENT112
Overall approach to data quality management implementation112
Senior-level sponsorship113
Understand the context114
Identify synergies115
Choose an implementation approach116
Agree the ‘footprint’116
Change management117
Ethical use of data119
Dealing with challenges and issues119
De-risk existing projects120
Securing budget and resources121
Starting implementation122
Summary123
12. THE HUMAN FACTOR – ENSURING PEOPLE SUPPORT DATA QUALITY MANAGEMENT124
People are the solution124
Behaviours and culture125
The employee data agreement126
Strategies for changing data behaviours127
Organisational influences on behaviours129
Summary131
Conclusions132
Bibliography134
Index136
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Figure 1.1 The components of a business activity5
Figure 1.2 A typical life cycle for general data8
Figure 1.3 A typical life cycle for documents10
Figure 2.1 The virtuous circle of data quality16
Figure 2.2 The data triangle19
Figure 3.1 Overview of the Data Zoo29
Figure 6.1 The ISO 8000-61 process model58
Figure 7.1 Capability Level 1 of data quality management61
Figure 7.2 Capability Level 2 of data quality management63
Figure 7.3 Capability Level 3 of data quality management65
Figure 7.4 Capability Level 4 of data quality management66
Figure 7.5 Capability Level 5 of data quality management67
Figure 7.6 Overall capability model for data