You're reading from Data Engineering with AWS - Second Edition

Product type Book

Published in Oct 2023

Publisher Packt

ISBN-13 9781804614426

Pages 636 pages

Edition 2nd Edition

Languages

Concepts

Data Engineering

Author (1):

Gareth Eagar

Table of Contents (24) Chapters

Preface

1. Section 1: AWS Data Engineering Concepts and Trends

2. An Introduction to Data Engineering

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

Hands-on – automated deployment of data platform components and data transformation code

While we do not have space to cover all aspects of building a modern data platform, in this section we will cover how to use various AWS services to deploy some components of a data platform. We start by setting up an AWS CodeCommit repository that will contain all the resources for our data repository (such as Glue ETL scripts and CloudFormation templates). We then use AWS CodePipeline to configure pipeline jobs that push any code or infrastructure changes into our target account.

Setting up a Cloud9 IDE environment

Our first step is to create a Cloud9 IDE environment, which we can use for writing our code and committing code to a CodeCommit repository. Cloud9 is an AWS service that can be used to provision a managed EC2 instance to provide us with a browser-based Integrated Development Environment (IDE) that we can use to write, run, and debug code from within our web browser...