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

AWS services for transforming data

Once your data is ingested into an appropriate AWS service, such as Amazon S3, the next stage of the pipeline needs to transform the data to optimize it for analytics and to make it available to your data consumers.Some of the tools we discussed in the previous section for ingesting data into AWS can perform light transformations as part of the ingestion process. For example, Amazon DMS can write out data in Parquet format (a format optimized for analytics), as can Kinesis Firehose. However, heavier transformations are often required to fully optimize your data for a differing set of analytic tasks and diverse data consumers, and in this section, we will examine some of the core AWS services that can be used for this.

Overview of AWS Lambda for light transformations

AWS Lambda provides a serverless environment for executing code, and is one of AWS's most popular services. You can trigger your Lambda function to execute your code in multiple ways...