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

Understanding QuickSight’s advanced features

The Enterprise edition of Amazon QuickSight includes advanced features that can help you draw out additional insights from your data, ask questions of your data using natural language, and enable you to widely share your data by embedding dashboards into applications. We will review some of these features next.

Amazon QuickSight ML Insights

QuickSight ML Insights uses the power of ML algorithms to automatically uncover insights and trends, forecast future data points, and identify anomalies in your data.

All of these ML Insights functionalities can easily be added to an analysis/dashboard without the author needing to have any ML experience or any real understanding of the underlying ML algorithms. However, for those who are interested in the underlying ML algorithms used by QuickSight, Amazon provides comprehensive documentation on this topic.

Review the Amazon QuickSight documentation titled Understanding the...