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

Chapter 1: An Introduction to Data Engineering

Data engineering is a fast-growing career path, and a role in high demand, as data becomes ever more critical to organizations of all sizes. For those that enjoy the challenge of putting together the "puzzle pieces" that build out complex data pipelines to ingest raw data, and to then transform and optimize that data for various data consumers, it can be a really rewarding career.

In this chapter, we look at the many ways that data has become an important and valuable corporate asset. We also review some of the challenges that organizations face as they deal with increasing volumes of data, and how data engineers can use cloud-based services to help overcome these challenges. We then set the foundations for the rest of the hands-on activities in this book by providing step-by-step details on creating a new Amazon Web Services (AWS) account.

Throughout this book, we are going to cover a number of topics that teach the fundamentals of developing data engineering pipelines on AWS, but we'll get started in this chapter with these topics:

  • The rise of big data as a corporate asset
  • The challenges of ever-growing datasets
  • The role of the data engineer as a big data enabler
  • The benefits of the cloud when building big data analytic solutions
  • Hands-on - create or access an AWS account for following along with the hands-on activities in this book