Data Engineering with AWS Cookbook 1st Edition

Grab the modern guide every data practitioner needs: Data Engineering with AWS Cookbook, 1st Edition by Trâm Ngọc Phạm. This practical, hands-on book delivers clear recipes for building robust, scalable data pipelines on AWS, whether you’re working in a startup in Ho Chi Minh City, an enterprise in London, or a cloud team anywhere worldwide.

Inside, you’ll find concise, real-world solutions for common data engineering challenges: fast data ingestion with Kinesis and S3, ETL and transformation using Glue and Lambda, cost-effective analytics with Redshift and Athena, and reliable orchestration with Step Functions. Each chapter breaks complex topics into step-by-step recipes that accelerate implementation and reduce trial-and-error—perfect for data engineers, architects, analytics developers, and technical leads.

What sets this cookbook apart is its focus on production readiness: performance tuning, security best practices, monitoring and observability, and patterns for scalability and fault tolerance. The tone is practical and approachable, bridging theory and hands-on AWS implementation so you can move from prototype to production with confidence.

Whether you’re upskilling for the cloud, optimizing existing pipelines, or designing new data platforms, this book provides targeted solutions and proven patterns to save time and lower operational risk. Make smarter decisions faster and unlock better insights from your data.

Order your copy of Data Engineering with AWS Cookbook today and start building resilient, efficient data architectures on AWS—designed for teams in Vietnam, Southeast Asia, and across the globe.

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