Learn data engineering and modern data pipeline design with AWS in this comprehensive guide! You will explore key AWS services like S3, Glue, Redshift, and QuickSight to ingest, transform, and analyze data, and you'll gain hands-on experience creating robust, scalable solutions. What this Book will help me do Understand and implement data ingestion and transformation processes using AWS tools. Optimize data for analytics with advanced AWS-powered workflows. Build end-to-end modern data pipelines leveraging cutting-edge AWS technologies. Design data governance strategies using AWS services for security and compliance. Visualize data and extract insights using Amazon QuickSight and other tools. Author(s) Gareth Eagar is a Senior Data Architect with over 25 years of experience in designing and implementing data solutions across various industries. He combines his deep technical expertise with a passion for teaching, aiming to make complex concepts approachable for learners at all levels. Who is it for? This book is intended for current or aspiring data engineers, data architects, and analysts seeking to leverage AWS for data engineering. It suits beginners with a basic understanding of data concepts who want to gain practical experience as well as intermediate professionals aiming to expand into AWS-based systems.

Discover how to effectively build and manage data engineering pipelines using AWS with "Data Engineering with AWS". In this hands-on book, you'll explore the foundational principles of data engineering, learn to architect data pipelines, and work with essential AWS services to process, transform, and analyze data. What this Book will help me do Understand and implement modern data engineering pipelines with AWS services. Gain proficiency in automating data ingestion and transformation using Amazon tools. Perform efficient data queries and analysis leveraging Amazon Athena and Redshift. Create insightful data visualizations using Amazon QuickSight. Apply machine learning techniques to enhance data engineering processes. Author(s) None Eagar, a Senior Data Architect with over twenty-five years of experience, specializes in modern data architectures and cloud solutions. With a rich background in applying data engineering to real-world problems, None Eagar shares expertise in a clear and approachable way for readers. Who is it for? This book is perfect for data engineers and data architects aiming to grow their expertise in AWS-based solutions. It's also geared towards beginners in data engineering wanting to adopt the best practices. Those with a basic understanding of big data and cloud platforms will find it particularly valuable, but prior AWS experience is not required.