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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
Author (1):
Gareth Eagar Gareth Eagar
Profile icon 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

Ingesting data from a relational database

A common source of data for analytical projects is data that comes from a relational database system such as MySQL, PostgreSQL, SQL Server, or an Oracle database. Organizations often have multiple siloed databases, and they want to bring the data from these varied databases into a central location for analytics.

It is common for these projects to include ingesting historical data that already exists in the database, as well as syncing ongoing new and changed data from the database. There are a variety of tools that can be used to ingest from database sources, as we will discuss in this section.

AWS DMS

The primary AWS service for ingesting data from a database is AWS DMS, though there are other ways to ingest data from a database source. As a data engineer, you need to evaluate both the source and the target to determine which ingestion tool will be best suited.

AWS DMS is intended for doing either one-off ingestion of historical...

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