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

Hands-on – ingesting data with AWS DMS

As we discussed earlier in this chapter, AWS DMS can be used to replicate a database into an Amazon S3-based data lake (among other uses). Follow the steps in this section to do the following:

  • Create a new MySQL database instance in your account.
  • Load a MySQL demo database using an EC2 instance.
  • Set up a DMS replication instance and configure endpoints and tasks.
  • Run the DMS full-load.
  • Run a Glue Crawler to add the tables that were newly loaded into S3 into the data catalog.
  • Query the data with Amazon Athena.

    Note

    The following steps assume the use of your AWS account's default VPC and security group. You will need to modify the steps as needed if you're not using the default.

Creating a new MySQL database instance

First, we will create a new MySQL database using the default easy create settings for a free tier eligible database instance:

  1. Log into the AWS Management Console (https:/...