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The Definitive Guide to Data Integration

You're reading from   The Definitive Guide to Data Integration Unlock the power of data integration to efficiently manage, transform, and analyze data

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Product type Paperback
Published in Mar 2024
Publisher Packt
ISBN-13 9781837631919
Length 490 pages
Edition 1st Edition
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Authors (4):
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Raphaël MANSUY Raphaël MANSUY
Author Profile Icon Raphaël MANSUY
Raphaël MANSUY
Pierre-Yves BONNEFOY Pierre-Yves BONNEFOY
Author Profile Icon Pierre-Yves BONNEFOY
Pierre-Yves BONNEFOY
Emeric CHAIZE Emeric CHAIZE
Author Profile Icon Emeric CHAIZE
Emeric CHAIZE
Mehdi TAZI Mehdi TAZI
Author Profile Icon Mehdi TAZI
Mehdi TAZI
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Toc

Table of Contents (19) Chapters Close

Preface 1. Chapter 1: Introduction to Our Data Integration Journey 2. Chapter 2: Introducing Data Integration FREE CHAPTER 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

A focus on APIs and strategy

The critical role of APIs in the realm of data integration is a subject of increasing importance. APIs, in essence, are sets of instructions or rules that enable different software applications to communicate and exchange data. They provide a structured method for diverse systems to interconnect, fostering a higher degree of interoperability among various software components. By offering a clear and consistent means for data exchange, APIs act as critical facilitators for seamless and efficient data integration.

Data integration itself is an essential process within the wider context of data management. It involves combining data from different sources into a unified, coherent view. This process is crucial for numerous tasks, from simple data analysis to more complex operations such as business intelligence, machine learning, and decision support systems. As the amount and variety of data grows, the importance of robust data integration strategies cannot...

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