Data Engineering with AWS 2nd Edition

Grab the future of cloud analytics with Data Engineering with AWS, 2nd Edition by Gareth Eagar — a practical, up-to-date guide that transforms AWS services into reliable, scalable data platforms. Whether you’re an engineer, architect, or analytics leader, this edition delivers clear, actionable strategies for building production-ready data pipelines in the cloud.

Discover step-by-step techniques for designing data lakes on Amazon S3, orchestrating ETL/ELT with AWS Glue, stream processing with Kinesis, batch workloads on EMR, and analytics at scale using Redshift. Eagar combines real-world patterns, architectural diagrams, and best practices for security, cost optimization, and governance so you can implement resilient solutions across teams and regions — from startups to enterprises in North America, Europe, and Asia-Pacific.

This edition emphasizes practical decision-making: how to choose serverless vs. managed services, automate deployments with IaC, and monitor data quality across pipelines. You’ll learn to avoid common pitfalls and accelerate time-to-insight with reproducible, maintainable workflows that support machine learning and BI use cases.

If you want to design robust, compliant, and cost-effective data platforms on AWS, this book gives you the tools and confidence to act. Packed with examples and patterns you can apply immediately, Data Engineering with AWS, 2nd Edition is the hands-on reference for modern data teams. Order now to future-proof your data architecture and lead your organization toward faster, smarter data-driven decisions.

Note: eBooks do not include supplementary materials such as CDs, access codes, etc.