You're reading from Data Engineering with AWS Acquire the skills to design and build AWS-based data transformation pipelines like a pro

Product type Paperback

Published in Oct 2023

Publisher Packt

ISBN-13 9781804614426

Length 636 pages

Edition 2nd Edition

Tools

AWS

Concepts

Data Engineering

Author (1):

Gareth Eagar

View More author details

Table of Contents (24) Chapters

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

Ingesting streaming data

An increasingly common source of data for analytic projects is data that is continually generated and needs to be ingested in near real time. Some common sources of this type of data are as follows:

Data from IoT devices (such as smartwatches, smart appliances, and so on)
Telemetry data from various types of vehicles (cars, airplanes, and so on)
Sensor data (from manufacturing machines, weather stations, and so on)
Live gameplay data from mobile games
Mentions of the company brand on various social media platforms

For example, Boeing, the aircraft manufacturer, has a system called Airplane Health Management (AHM) that collects in-flight airplane data and relays it in real time to Boeing systems. Boeing processes the information and makes it immediately available to airline maintenance staff via a web portal.

In this section, we will look at several tools and services for ingesting streaming data, as well as things...