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Data Engineering with AWS - Second Edition

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
Author (1):
Gareth Eagar Gareth Eagar
Profile icon Gareth Eagar
LinkedIn
Gareth Eagar has over 25 years of experience in the IT industry, starting in South Africa, working in the United Kingdom for a while, and now based in the USA. Having worked at AWS since 2017, Gareth has broad experience with a variety of AWS services, and deep expertise around building data platforms on AWS. While Gareth currently works as a Solutions Architect, he has also worked in AWS Professional Services, helping architect and implement data platforms for global customers. Gareth frequently speaks on data related topics.
See other products by 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 – ingesting streaming data

Earlier in this chapter, we looked at two options for ingesting streaming data into AWS, namely Amazon Kinesis and Amazon MSK. AWS provides an open-source solution for streaming sample data to Amazon Kinesis; therefore, in this section, we will use the Amazon Kinesis service to ingest streaming data. To generate streaming data, we will use the AWS open-source Amazon Kinesis Data Generator (KDG).

In this section, we will perform the following tasks:

  1. Configure Amazon Kinesis Data Firehose to ingest streaming data, and write the data out to Amazon S3.
  2. Configure Amazon KDG to create mock streaming data.

To get started, let’s configure a new Kinesis Data Firehose instance to ingest streaming data and write it out to our Amazon S3 data lake.

Configuring Kinesis Data Firehose for streaming delivery to Amazon S3

Kinesis Data Firehose is designed to enable you to easily ingest data from streaming sources...

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Authors (1)

Profile icon Gareth Eagar
LinkedIn
Gareth Eagar has over 25 years of experience in the IT industry, starting in South Africa, working in the United Kingdom for a while, and now based in the USA. Having worked at AWS since 2017, Gareth has broad experience with a variety of AWS services, and deep expertise around building data platforms on AWS. While Gareth currently works as a Solutions Architect, he has also worked in AWS Professional Services, helping architect and implement data platforms for global customers. Gareth frequently speaks on data related topics.
See other products by Gareth Eagar

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