Data Engineering

Catalog description

The course provides an in-depth knowledge of data technologies and scalable architectures available through the framework of the data engineering lifecycle, as well as the integration of a variety of cloud technologies to serve the needs of downstream data consumers. You will learn how to apply the concepts of data generation, ingestion, transformation, storage, serving data for BI analytics and ML, and governance that are critical to any data environment. You will assess different data engineering problems, design and build end-to-end frameworks, such as event-driven and streaming systems, data pipeline orchestration, parallel computing frameworks, containerization, cloud services and cloud-native computing technologies. Prior familiarity with the Python programming language is required, and knowledge of databases and SQL is recommended. Offered as CSDS 317 and CSDS 417 . Prereq: Graduate student standing.