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Data Engineering with AWS

You're reading from   Data Engineering with AWS Acquire the skills to design and build AWS-based data transformation pipelines like a pro

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Product type Paperback
Published in Oct 2023
Publisher Packt
ISBN-13 9781804614426
Length 636 pages
Edition 2nd Edition
Tools
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Author (1):
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Gareth Eagar Gareth Eagar
Author Profile Icon Gareth Eagar
Gareth Eagar
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Table of Contents (24) Chapters Close

Preface 1. Section 1: AWS Data Engineering Concepts and Trends
2. An Introduction to Data Engineering FREE CHAPTER 3. Data Management Architectures for Analytics 4. The AWS Data Engineer’s Toolkit 5. Data Governance, Security, and Cataloging 6. Section 2: Architecting and Implementing Data Engineering Pipelines and Transformations
7. Architecting Data Engineering Pipelines 8. Ingesting Batch and Streaming Data 9. Transforming Data to Optimize for Analytics 10. Identifying and Enabling Data Consumers 11. A Deeper Dive into Data Marts and Amazon Redshift 12. Orchestrating the Data Pipeline 13. Section 3: The Bigger Picture: Data Analytics, Data Visualization, and Machine Learning
14. Ad Hoc Queries with Amazon Athena 15. Visualizing Data with Amazon QuickSight 16. Enabling Artificial Intelligence and Machine Learning 17. Section 4: Modern Strategies: Open Table Formats, Data Mesh, DataOps, and Preparing for the Real World
18. Building Transactional Data Lakes 19. Implementing a Data Mesh Strategy 20. Building a Modern Data Platform on AWS 21. Wrapping Up the First Part of Your Learning Journey 22. Other Books You May Enjoy
23. Index

Building generative AI solutions on AWS

In November 2022, a company called OpenAI launched ChatGPT, a chatbot built on a new type of ML technology. This very quickly went viral and became a world-wide sensation, as people were amazed at the ability of this new chatbot to have conversations on just about any topic. OpenAI explained the abilities of this new chatbot as follows:

We’ve trained a model called ChapGPT which interacts in a conversational way. The dialogue format makes it possible for ChaptGPT to answer follow-up questions, admit its mistakes, challenge incorrect premises, and reject inappropriate requests.

Using AWS services, it is possible for anyone to create new solutions or services that take advantage of the same type of technology that powers ChatGPT. But before we get into the AWS services that can be used for generative AI, let’s have a brief look at the details of the technology behind these new machine learning services.

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