Search icon CANCEL
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
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

Arrow left icon
Product type Paperback
Published in Oct 2023
Publisher Packt
ISBN-13 9781804614426
Length 636 pages
Edition 2nd Edition
Tools
Arrow right icon
Author (1):
Arrow left icon
Gareth Eagar Gareth Eagar
Author Profile Icon Gareth Eagar
Gareth Eagar
Arrow right icon
View More author details
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 – orchestrating a data pipeline using AWS Step Functions

In this section, we will get hands-on with the AWS Step Functions service, which can be used to orchestrate data pipelines. The pipeline we’re going to orchestrate is relatively simple, but Step Functions can also be used to orchestrate far more complex pipelines with many steps. To keep things simple, we will only use Lambda functions to process our data, but you could replace Lambda functions with Glue jobs in production pipelines that need to process large amounts of data.

For our Step Functions state machine, let’s start by running a Lambda function that checks the extension of an incoming file to determine the type of file. Once determined, we’ll pass that information on to the next state, which is a CHOICE state. If it is a file type we support, we’ll call a Lambda function to process the file, but if it’s not, we’ll send out a notification, indicating that...

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime