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

Product type Paperback

Published in Oct 2023

Publisher Packt

ISBN-13 9781804614426

Length 636 pages

Edition 2nd Edition

Tools

AWS

Concepts

Data Engineering

Author (1):

Gareth Eagar

View More author details

Table of Contents (24) Chapters

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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