Book Image

Data Engineering with AWS

By : Gareth Eagar
Book Image

Data Engineering with AWS

By: Gareth Eagar

Overview of this book

Written by a Senior Data Architect with over twenty-five years of experience in the business, Data Engineering for AWS is a book whose sole aim is to make you proficient in using the AWS ecosystem. Using a thorough and hands-on approach to data, this book will give aspiring and new data engineers a solid theoretical and practical foundation to succeed with AWS. As you progress, you’ll be taken through the services and the skills you need to architect and implement data pipelines on AWS. You'll begin by reviewing important data engineering concepts and some of the core AWS services that form a part of the data engineer's toolkit. You'll then architect a data pipeline, review raw data sources, transform the data, and learn how the transformed data is used by various data consumers. You’ll also learn about populating data marts and data warehouses along with how a data lakehouse fits into the picture. Later, you'll be introduced to AWS tools for analyzing data, including those for ad-hoc SQL queries and creating visualizations. In the final chapters, you'll understand how the power of machine learning and artificial intelligence can be used to draw new insights from data. By the end of this AWS book, you'll be able to carry out data engineering tasks and implement a data pipeline on AWS independently.
Table of Contents (19 chapters)
1
Section 1: AWS Data Engineering Concepts and Trends
6
Section 2: Architecting and Implementing Data Lakes and Data Lake Houses
13
Section 3: The Bigger Picture: Data Analytics, Data Visualization, and Machine Learning

Understanding Amazon QuickSight's core concepts

At its core, QuickSight lets us ingest data from a wide variety of sources, perform some filtering or other transformation tasks on the data, and then create dashboards with multiple types of visuals that can be easily shared with others.

The QuickSight service is fully managed by AWS, and there are no upfront costs for using the service. Instead, the service uses a pricing model of a monthly cost per user and offers both Standard and Enterpise Editions. QuickSight also includes a powerful in-memory storage and computation engine to enable the best performance for working with a variety of data sources.

In this section, we'll examine the differences between the standard and enterprise editions of QuickSight and also do a deeper dive into SPICE, the in-memory storage and computation engine.

Standard versus enterprise edition

The Standard Edition of QuickSight is useful for those that are just starting to explore...