Designing Cloud Data Platforms (1 ed)

In Designing Cloud Data Platforms, Danil Zburivsky and Lynda Partner present a six-layer approach that enhances flexibility while reducing costs. You’ll explore effective patterns for ingesting data from diverse sources and learn how to leverage pre-built services offered by cloud providers to build robust, scalable data platforms.

Inside this book:

• Best practices for managing structured and unstructured datasets
• Cloud-ready machine learning tools
• Metadata management and real-time analytics
• Defensive architecture, access control, and security

This book serves as a practical guide for data engineers and anyone designing modern cloud data platforms, with a focus on performance, security, and flexibility for handling today’s complex data workloads.