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Modern Data Architecture on AWS

You're reading from Modern Data Architecture on AWS

Product type Book

Published in Aug 2023

Publisher Packt

ISBN-13 9781801813396

Pages 420 pages

Edition 1st Edition

Languages

Concepts

Author (1):

Behram Irani

Table of Contents (24) Chapters

Preface

1. Part 1: Foundational Data Lake

2. Prologue: The Data and Analytics Journey So Far

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

Why subscribe?

23. Other Books You May Enjoy

Modern Data Architecture on AWS

Before we dive deep into the actual data and analytics use cases and how to design and build them, let’s address the elephant in the room—what is a modern data architecture, and why build it on Amazon Web Services (AWS)?

One of the fundamental tenets of a modern data architecture on AWS is to seamlessly integrate your data lake, data warehouse, and purpose-built data stores. In the previous prologue, we looked at what a data warehouse is and what it does. We also looked at the data tier in a three-tier architecture, typically referred to as a relational database management system (RDBMS) and considered a type of purpose-built store. The type of system we haven’t really explored in much detail yet is the data lake. The next chapter is completely dedicated to data lakes, but before we go any further in this chapter, it is important to get some context around the need for data lakes in the first place.

In this chapter, we will...

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Authors (1)

Behram Irani

Behram Irani is currently a technology leader with Amazon Web Services (AWS) specializing in data, analytics and AI/ML. He has spent over 18 years in the tech industry helping organizations, from start-ups to large-scale enterprises, modernize their data platforms. In the last 6 years working at AWS, Behram has been a thought leader in the data, analytics and AI/ML space; publishing multiple papers and leading the digital transformation efforts for many organizations across the globe. Behram has completed his Bachelor of Engineering in Computer Science from the University of Pune and has an MBA degree from the University of Florida.

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