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 – reviewing reviews with Amazon Comprehend

Imagine that you work for a large hotel chain and have been tasked with developing a process for identifying negative reviews that have been posted on your website. This will help the customer service teams follow up with the customer.

If your company was getting hundreds of reviews every day, it would be time-consuming to have someone read the entire review every time a new review was posted. Luckily, you have recently heard about Amazon Comprehend, so you decide to develop a small Proof of Concept (PoC) test to see whether Amazon Comprehend can help.

If your PoC is successful, you will want to have a decoupled process that receives reviews once they have been posted, calls Amazon Comprehend to determine the sentiment of the review, and then takes a follow-up action if the review is negative or mixed. Therefore, you decide to build your PoC in the same way, using Amazon Simple Queue Service (SQS) to receive reviews...