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Modern Data Architecture on AWS

You're reading from   Modern Data Architecture on AWS A Practical Guide for Building Next-Gen Data Platforms on AWS

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Product type Paperback
Published in Aug 2023
Publisher Packt
ISBN-13 9781801813396
Length 420 pages
Edition 1st Edition
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Author (1):
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Behram Irani Behram Irani
Author Profile Icon Behram Irani
Behram Irani
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Table of Contents (24) Chapters Close

Preface 1. Part 1: Foundational Data Lake
2. Prologue: The Data and Analytics Journey So Far FREE CHAPTER 3. Chapter 1: Modern Data Architecture on AWS 4. Chapter 2: Scalable Data Lakes 5. Part 2: Purpose-Built Services And Unified Data Access
6. Chapter 3: Batch Data Ingestion 7. Chapter 4: Streaming Data Ingestion 8. Chapter 5: Data Processing 9. Chapter 6: Interactive Analytics 10. Chapter 7: Data Warehousing 11. Chapter 8: Data Sharing 12. Chapter 9: Data Federation 13. Chapter 10: Predictive Analytics 14. Chapter 11: Generative AI 15. Chapter 12: Operational Analytics 16. Chapter 13: Business Intelligence 17. Part 3: Govern, Scale, Optimize And Operationalize
18. Chapter 14: Data Governance 19. Chapter 15: Data Mesh 20. Chapter 16: Performant and Cost-Effective Data Platform 21. Chapter 17: Automate, Operationalize, and Monetize 22. Index 23. Other Books You May Enjoy

Data mesh concepts

If you recall from Chapter 8, Data Sharing, we kept the important topic of a distributed data lake that spans multiple AWS accounts open-ended. Now is a good time to complete that story. Even today, the vast majority of use cases that require a data lake can be solved by building a centralized data lake. However, as organizations become bigger, new lines of businesses (LOBs) that work as autonomous units become a reality. All these LOBs add more data sources to grow their business units, resulting in the exponential growth of data at the enterprise level.

Sharing data within an enterprise presents its fair share of challenges. Different LOBs have invested in cloud-based data lakes, along with customized analytics solutions, tailored to address their specific business needs. However, these systems are often designed to cater to particular types of data and may not seamlessly translate to other problem domains.

For many large organizations with many LOBs, a centralized...

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