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Data quality : empowering businesses with analytics and AI (2023)

Southekal, Prashanth H.,

Hoboken, New Jersey :John Wiley & Sons, Inc.,

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Details

UID:

almahu_9949891168502882

Umfang: 1 online resource (xxvi, 271 pages) : , illustrations (chiefly color)

ISBN: 9781394165247 , 1394165242 , 9781394165254 , 1394165250

Inhalt: "Quality data is the key for business enterprises to offer improved performance in operations, compliance, and decision making. According to McKinsey, data driven organizations provide EBITDA increases between 15 to 25% than peers. However, to be a data driven organization, data quality is very important. But most companies are plagued with poor data quality. A HBR study found that just 3% of the data in a business enterprise meets quality standards. According to Gartner, 27% of data in the world's top companies is flawed--so companies are looking for practical guidance to improve data quality. This book examines the four-phase DARS approach (Define-Assess-Realize-Sustain) for companies to manage high quality data in organizations. This approach provides a combination of strategy and tactical elements to deliver the greatest value from data to the business. It is a playbook that offers prescriptive recommendations based on proven best practices to realize and sustain data quality"--

Anmerkung: Business data -- Data quality in business -- Causes for poor data quality -- Data lifecycle and lineage -- Profiling for data quality -- Reference architecture for data quality -- Best practices to realize data quality -- Best practices to realize data quality -- Data governance -- Protecting data -- Data ethics.

Weitere Ausg.: Print version: Southekal, Prashanth H. Data quality Hoboken, New Jersey : Wiley, [2023] ISBN 9781394165230

Sprache: Englisch

URL: https://onlinelibrary.wiley.com/doi/book/10.1002/9781394320547

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Bibliothek	Standort	Signatur	Band/Heft/Jahr	Verfügbarkeit

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Online-Ressource

HU Berlin

FU Berlin

Online-Ressource

Data quality : empowering businesses with analytics and AI (2023)

Southekal, Prashanth H. [Verfasser]

Newark : Wiley

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Details

UID:

b3kat_BV048831589

Umfang: 1 Online-Ressource (xxvi, 271 Seiten) , Illustrationen

ISBN: 9781394165247

Anmerkung: 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.

Weitere Ausg.: Erscheint auch als Druck-Ausgabe Southekal, Prashanth Data Quality Newark : John Wiley & Sons, Incorporated,c2023 ISBN 9781394165230

Weitere Ausg.: Erscheint auch als Online-Ausgabe, PDF ISBN 9781394165254

Sprache: Englisch

Fachgebiete: Informatik

RVK:

ST 505

Schlagwort(e): Datenanalyse ; Datenqualität ; Datenmanagement

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Bibliothek	Standort	Signatur	Band/Heft/Jahr	Verfügbarkeit

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Online-Ressource

HWR Berlin

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