The book's central framework is the , which provides a holistic view of how data moves from production to consumption. This lifecycle consists of five key stages: Generation: Understanding source systems. Ingestion: Moving data from sources into storage. Storage: Choosing the right architecture for persistence. Transformation: Cleaning and modeling data for use.
Kafka, Flink, and real-time processing are covered at 30,000 ft. You’ll understand when to use streaming, but not how . Fundamentals of Data Engineering by Joe Reis PDF
It provides a comprehensive overview of the entire data engineering landscape, helping engineers assess problems and design robust architectures that meet organizational needs. The book's central framework is the , which