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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 warehouse modernization using Redshift

We will start with the most obvious high-level use case: organizations that want to modernize their data warehouses. The primary reason to modernize is that traditional data warehouses are unable to keep up with the new emerging use cases. Due to their architectural limitations, traditional data warehouses are not able to handle the exponential growth in data volume along with the new variety of data that’s being produced. Long story short, traditional data warehouses have become slow, complex, and expensive. Let’s bring up the use case from GreatFin again.

Use case for data warehouse modernization

GreatFin has an on-premises data warehouse that is nearing its end of life. The continuous requests from businesses to support newer types of data analytics use cases have made this platform difficult to operate and expand. Its performance is becoming slow and the infrastructure and operating expenses are growing steadily. They...

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