Managing Data Quality: A Practical Guide
- Length: 158 pages
- Edition: 1
- Language: English
- Publisher: BCS
- Publication Date: 2020-02-14
- ISBN-10: 1780174594
- ISBN-13: 9781780174594
- Sales Rank: #2493205 (See Top 100 Books)
Data is an increasingly important business asset and enabler for organisational activities. Data quality is a key aspect of data management and failure to understand it increases organisational risk and decreases efficiency and profitability. This book explains data quality management in practical terms, focusing on three key areas – the nature of data in enterprises, the purpose and scope of data quality management, and implementing a data quality management system, in line with ISO 8000-61.
Front Cover Half-Title Page BCS, THE CHARTERED INSTITUTE FOR IT Title Page Copyright Page Contents List of figures and tables Authors Acknowledgements Abbreviations Glossary Preface Part I: The Challenge of Enterprise Data 1. The Data Asset What are data? What is data quality? What is data quality management? Summary 2. Challenges When Exploiting and Managing Data The complex data landscape Complex decisions Virtuous circle or downward spiral? Unclear data ownership Backups and data quality Data quality and lack of transparency in business cases The data triangle Data as a raw material The data machine: expectations vs reality Do your data trust you? The challenge of managing enterprise data quality Summary 3. The Impact of People on Data Quality Comparisons between data quality and health and safety People and data The Data Zoo How data behaviours interact Individuals as part of a team Teams within the organisation Data demotivators Summary 4. Case Studies and Examples Real-world examples of the impacts of poor data Case study – Mars Climate Orbiter Case study – Maintenance productivity targets degrading data quality Case study – Railtrack Case study – Statutory reporting Case study – Oversized trains Case study – Retail fail Case study – Inappropriate controls and haste degraded data quality Summary Part II: A Framework For Data Quality Management 5. The Purpose and Scope of Data Quality Management The difference between data management and data quality management Key principles for data quality management Summary 6. The ISO 8000-61 Approach The scope of ISO 8000-61 The processes in ISO 8000-61 Summary 7. Data Quality Management Capability Levels Capability Level 1 Capability Level 2 Capability Level 3 Capability Level 4 Capability Level 5 Overall capability model Summary 8. ISO 8000-61 Processes Data processing Provision of data specifications and work instructions Data quality monitoring and control Data quality planning Data-related support Resource provision Data quality assurance Data quality improvement Summary 9. The Maturity Journey Planning the journey Assessing maturity Summary Part III: Implementing Data Quality Management 10. Preparing The Organisation For Data Quality Management What does a data-enabled organisation look like? Improvement opportunities in typical organisations The data quality management journey The case for change The changing organisation The role of the chief data officer Preparing the organisation Summary 11. Implementing Data Quality Management Overall approach to data quality management implementation Senior-level sponsorship Understand the context Identify synergies Choose an implementation approach Agree the ‘footprint’ Change management Ethical use of data Dealing with challenges and issues De-risk existing projects Securing budget and resources Starting implementation Summary 12. The Human Factor – Ensuring People Support Data Quality Management People are the solution Behaviours and culture The employee data agreement Strategies for changing data behaviours Organisational influences on behaviours Summary Conclusions Bibliography Index Back Cover
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