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

AWS services for ingesting data

The first step in building big data analytic solutions is to ingest data from a variety of sources into AWS. In this section, we introduce some of the core AWS services designed to help with this; however, this should not be considered a comprehensive review of every possible way to ingest data into AWS.

Don't feel overwhelmed by the number of services we cover in this section! We will explore approaches for deciding on the right service for your specific use case in later chapters, but it is important to have a good understanding of the available tools upfront.

Overview of Amazon Database Migration Service (DMS)

One of the most common ingestion use cases is to sync data from a traditional database system into an analytic pipeline, either landing the data in an Amazon S3-based data lake, or in a data warehousing system such as Amazon Redshift.

Amazon DMS is a versatile tool that can be used to migrate existing database systems to a new...