Format:
1 Online-Ressource (xxvi, 271 Seiten)
,
Illustrationen
ISBN:
9781394165247
Note:
Cover -- Title Page -- Copyright Page -- Contents -- Foreword -- Preface -- Acknowledgments -- Part I Define Phase -- Chapter 1 Introduction -- Introduction -- Data, Analytics, AI, and Business Performance -- Data as a Business Asset or Liability -- Data Governance, Data Management, and Data Quality -- Leadership Commitment to Data Quality -- Key Takeaways -- Conclusion -- References -- Chapter 2 Business Data -- Introduction -- Data in Business -- Telemetry Data -- Purpose of Data in Business -- Business Data Views -- Key Characteristics of Business Data -- Critical Data Elements (CDEs) -- Key Takeaways -- Conclusion -- References -- Chapter 3 Data Quality in Business -- Introduction -- Data Quality Dimensions -- Context in Data Quality -- Consequences and Costs of Poor Data Quality -- Data Depreciation and Its Factors -- Data in IT Systems -- Data Quality and Trusted Information -- Key Takeaways -- Conclusion -- References -- Part II Analyze Phase -- Chapter 4 Causes for Poor Data Quality -- Introduction -- Data Quality RCA Techniques -- Typical Causes of Poor Data Quality -- Key Takeaways -- Conclusion -- References -- Chapter 5 Data Lifecycle and Lineage -- Introduction -- Business-Enabled DLC Stages -- IT Business-Enabled DLC Stages -- Data Lineage -- Key Takeaways -- Conclusion -- References -- Chapter 6 Profiling for Data Quality -- Introduction -- Criteria for Data Profiling -- Data Profiling Techniques for Measures of Centrality -- Data Profiling Techniques for Measures of Variation -- Integrating Centrality and Variation KPIs -- Key Takeaways -- Conclusion -- References -- Part III Realize Phase -- Chapter 7 Reference Architecture for Data Quality -- Introduction -- Options to Remediate Data Quality -- DataOps -- Data Product -- Data Fabric and Data Mesh -- Data Enrichment -- Key Takeaways -- Conclusion -- References
,
Chapter 8 Best Practices to Realize Data Quality -- Introduction -- Overview of Best Practices -- BP 1: Identify the Business KPIs and the Ownership of These KPIs and the Pertinent Data -- BP 2: Build and Improve the Data Culture and Literacy in the Organization -- BP 3: Define the Current and Desired State of Data Quality -- BP 4: Follow the Minimalistic Approach to Data Capture -- BP 5: Select and Define the Data Attributes for Data Quality -- BP 6: Capture and Manage Critical Data with Data Standards in MDM Systems -- Key Takeaways -- Conclusion -- References -- Chapter 9 Best Practices to Realize Data Quality -- Introduction -- BP 7: Rationalize and Automate the Integration of Critical Data Elements -- BP 8: Define the SoR and Securely Capture Transactional Data in the SoR/OLTP System -- BP 9: Build and Manage Robust Data Integration Capabilities -- BP 10: Distribute Data Sourcing and Insight Consumption -- Key Takeaways -- Conclusion -- References -- Part IV Sustain Phase -- Chapter 10 Data Governance -- Introduction -- Data Governance Principles -- Data Governance Design Components -- Implementing the Data Governance Program -- Data Observability -- Data Compliance - ISO 27001, SOC1, and SOC2 -- Key Takeaways -- Conclusion -- References -- Chapter 11 Protecting Data -- Introduction -- Data Classification -- Data Safety -- Data Security -- Key Takeaways -- Conclusion -- References -- Chapter 12 Data Ethics -- Introduction -- Data Ethics -- Importance of Data Ethics -- Principles of Data Ethics -- Model Drift in Data Ethics -- Data Privacy -- Managing Data Ethically -- Key Takeaways -- Conclusion -- References -- Appendix 1: Abbreviations and Acronyms -- Appendix 2: Glossary -- Appendix 3: Data Literacy Competencies -- About the Author -- Index -- EULA.
Additional Edition:
Erscheint auch als Druck-Ausgabe Southekal, Prashanth Data Quality Newark : John Wiley & Sons, Incorporated,c2023 ISBN 9781394165230
Additional Edition:
Erscheint auch als Online-Ausgabe, PDF ISBN 9781394165254
Language:
English
Subjects:
Computer Science
Keywords:
Datenanalyse
;
Datenqualität
;
Datenmanagement
