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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 Section 1: AWS Data Engineering Concepts and Trends
An Introduction to Data Engineering Data Management Architectures for Analytics The AWS Data Engineer’s Toolkit Data Governance, Security, and Cataloging Section 2: Architecting and Implementing Data Engineering Pipelines and Transformations
Architecting Data Engineering Pipelines Ingesting Batch and Streaming Data Transforming Data to Optimize for Analytics Identifying and Enabling Data Consumers A Deeper Dive into Data Marts and Amazon Redshift Orchestrating the Data Pipeline Section 3: The Bigger Picture: Data Analytics, Data Visualization, and Machine Learning
Ad Hoc Queries with Amazon Athena Visualizing Data with Amazon QuickSight Enabling Artificial Intelligence and Machine Learning Section 4: Modern Strategies: Open Table Formats, Data Mesh, DataOps, and Preparing for the Real World
Building Transactional Data Lakes Implementing a Data Mesh Strategy Building a Modern Data Platform on AWS Wrapping Up the First Part of Your Learning Journey Other Books You May Enjoy
Index

Identifying data sources and ingesting data

With an understanding of the overall business goals for the project, and having identified our data consumers, we can start exploring the available data sources.

While most data sources will be internal to an organization, some projects may require enriching organization-owned data with other third-party data sources. Today, there are many data marketplaces where diverse datasets can be subscribed to or, in some cases, accessed for free. When discussing data sources, both internal and external datasets should be considered.

The team that has been included in the workshop should include people who understand the data sources required for the project. Some of the information that the data engineer needs to gather about these data sources includes the following:

  • Details about the source system containing data (is the data in a database, in files on a server, existing files on Amazon S3, coming from a streaming source, and...
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