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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

Streaming data ingestion using Amazon Kinesis

Amazon Kinesis was created specifically to alleviate all the pain points associated with setting up and operating a streaming platform. Organizations want to build real-time streaming data pipelines that make it easy to collect, process, and analyze data in real time. That’s what Kinesis brings to the table. It’s a serverless, fully managed, and scalable service for handling real-time streaming use cases. It seamlessly integrates with other AWS services and you only pay for what you use.

There are a lot of use cases that do different things with streaming data. Some use cases require the data to be processed and analyzed with the lowest latency possible; some use cases can withstand some delays in getting the data but expect the data to be compacted and aggregated for query efficiency; and some use cases require the data to be analyzed as it’s passing through the stream itself.

As you may recall, one of the tenants...

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