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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

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Since we will not be able to dive deep into every use case across many industries, the least we can do is highlight how GenAI can disrupt the conventional ways of solving use cases across many sectors. Every organization wants to ensure that it can transform its business outcomes by incorporating GenAI into its operations. Every industry has many low-hanging use cases where GenAI can accelerate its business outcomes.

Financial services

Since our book revolves around GreatFin, a financial conglomerate, let’s start with how GenAI helps solve several important but tedious use cases within the financial services industry. Here are some examples:

  • Fraud detection: GenAI can play a crucial role in identifying and preventing fraudulent activities in financial transactions. By analyzing extensive datasets, generative models can detect patterns and anomalies, enabling the identification of suspicious transactions and the...
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