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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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Toc

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

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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