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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

Data architectures

It’s critical to comprehend the significance of data architectures as we go further into the field of data storage. The designs for organizing, storing, and managing data within a company are known as data architectures. They assist in ensuring that data is effectively kept, readily available, and well-integrated across numerous systems. We will introduce data architectures in this section and go through the significance of logical and physical layer separation, as well as the value of data modeling.

Let’s start by defining the distinction between data architectures and data storage technologies. The foundational technologies that are used to store and manage data include data lakes, data warehouses, and object storage. However, the structure, organization, distribution, and design principles that control how data is stored, retrieved, and modified within those systems are provided by data architectures.

Here are some of the advantages of a well...

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