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The Definitive Guide to Data Integration

You're reading from  The Definitive Guide to Data Integration

Product type Book
Published in Mar 2024
Publisher Packt
ISBN-13 9781837631919
Pages 490 pages
Edition 1st Edition
Languages
Authors (4):
Pierre-Yves BONNEFOY Pierre-Yves BONNEFOY
Profile icon Pierre-Yves BONNEFOY
Emeric CHAIZE Emeric CHAIZE
Profile icon Emeric CHAIZE
Raphaël MANSUY Raphaël MANSUY
Profile icon Raphaël MANSUY
Mehdi TAZI Mehdi TAZI
Profile icon Mehdi TAZI
View More author details

Table of Contents (19) Chapters

Preface 1. Chapter 1: Introduction to Our Data Integration Journey 2. Chapter 2: Introducing Data Integration 3. Chapter 3: Architecture and History of Data Integration 4. Chapter 4: Data Sources and Types 5. Chapter 5: Columnar Data Formats and Comparisons 6. Chapter 6: Data Storage Technologies and Architectures 7. Chapter 7: Data Ingestion and Storage Strategies 8. Chapter 8: Data Integration Techniques 9. Chapter 9: Data Transformation and Processing 10. Chapter 10: Transformation Patterns, Cleansing, and Normalization 11. Chapter 11: Data Exposition and APIs 12. Chapter 12: Data Preparation and Analysis 13. Chapter 13: Workflow Management, Monitoring, and Data Quality 14. Chapter 14: Lineage, Governance, and Compliance 15. Chapter 15: Various Architecture Use Cases 16. Chapter 16: Prospects and Challenges 17. Index 18. Other Books You May Enjoy

Future challenges and opportunities of data integration

As we navigate the current landscape of data integration, it’s imperative to cast our gaze forward. The future holds both unprecedented challenges and unique opportunities in this domain. Grasping these nuances will enable us to adapt and innovate, ensuring that we remain at the forefront of data integration advancements.

The evolving landscape of data integration

The data integration ecosystem continues to rapidly evolve as new technologies emerge and architectures shift, such as cloud-native integration, data mesh, and data virtualization. To thrive amidst ongoing change, cross-functional collaboration is crucial to align technical teams and business stakeholders.

Mature data governance and stewardship also grow more critical to ensure quality outcomes as methods change. Forward-looking organizations that build organizational partnerships along with technical capacity will successfully adapt integration approaches...

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