Evaluating trade-offs and designing for agility and scalability. Orchestration: Scheduling and managing complex workflows.
Instead of focusing on specific tools like Hadoop or Spark, Reis and Housley organize the discipline around the . This framework identifies five primary stages that turn raw data into valuable products:
Fundamentals of Data Engineering by Joe Reis and Matt Housley is widely regarded as the "prequel" to the technical deep-dive of Designing Data-Intensive Applications . Published by O'Reilly Media in 2022, this book provides a technology-agnostic framework for building robust, scalable data systems in the modern cloud era. Core Concept: The Data Engineering Lifecycle Fundamentals of Data Engineering by Joe Reis PDF
Delivering data for analytics, machine learning, and business intelligence. The Six "Undercurrents"
Managing access control and protecting sensitive information. This framework identifies five primary stages that turn
Understanding source systems and how data is created.
The book emphasizes that data engineering isn't just about the lifecycle stages; it also requires managing six "undercurrents" that run through every project: and business intelligence.
Choosing appropriate storage abstractions (e.g., Data Lakes, Data Warehouses). Ingestion: Moving data from sources into storage.