You're reading from Data Engineering with AWS Learn how to design and build cloud-based data transformation pipelines using AWS

Product type Paperback

Published in Dec 2021

Publisher Packt

ISBN-13 9781800560413

Length 482 pages

Edition 1st Edition

Languages

Python

Tools

AWS

Concepts

Data Analysis

Author (1):

Gareth Eagar

View More author details

Table of Contents (19) Chapters

Preface

1. Section 1: AWS Data Engineering Concepts and Trends

2. Chapter 1: An Introduction to Data Engineering FREE CHAPTER

3. Chapter 2: Data Management Architectures for Analytics

4. Chapter 3: The AWS Data Engineer's Toolkit

5. Chapter 4: Data Cataloging, Security, and Governance

6. Section 2: Architecting and Implementing Data Lakes and Data Lake Houses

7. Chapter 5: Architecting Data Engineering Pipelines

8. Chapter 6: Ingesting Batch and Streaming Data

9. Chapter 7: Transforming Data to Optimize for Analytics

10. Chapter 8: Identifying and Enabling Data Consumers

11. Chapter 9: Loading Data into a Data Mart

12. Chapter 10: Orchestrating the Data Pipeline

13. Section 3: The Bigger Picture: Data Analytics, Data Visualization, and Machine Learning

14. Chapter 11: Ad Hoc Queries with Amazon Athena

15. Chapter 12: Visualizing Data with Amazon QuickSight

16. Chapter 13: Enabling Artificial Intelligence and Machine Learning

17. Chapter 14: Wrapping Up the First Part of Your Learning Journey

18. Other Books You May Enjoy

The AWS Glue/Lake Formation data catalog

As discussed previously, the AWS Glue catalog is a technical data catalog that can capture some business attributes using key/value tags. For example, you can have a key called data_owner and an associated value as a tag on each table in the catalog.

Within AWS, there are two services for interacting with the data catalog. So far, we have only discussed the AWS Glue service, but the AWS Lake Formation service also provides an interface for the same catalog.

It is important to understand that there is only a single data catalog, but that both Glue and Lake Formation provide an interface to the catalog. For example, if you set zone:curated as a table property on the film_category table in curatedzonedb using the Glue console, you will see that same property set when viewing the table using Lake Formation.

Here, we can see the table details for the film_category table in the AWS Glue console, and we can see that one of the tags on this...