The area of systems includes expertise in infrastructure systems and architectures to support working with big data — big in terms of volume, velocity, and variety — and building high performance pipelines in both development and production environments.
It includes the broad areas of hardware and software as such — computer technology as opposed to computer science. Key activities include developing cloud resources, building performant pipelines to ingest and aggregate data, developing networks of resilient distributed data, and writing and using software to accomplish tasks.
- Key tensions: development vs production, volume vs speed.
- Common theme: building
- Realm: concrete machinery.
- Keywords: infrastructure, data systems, data engineering, the cloud, networks, hardware, software, programming languages, big data management, benchmarking, continuous integration, availability, cybersecurity.
- Values: speed, stability, robustness, resilience, uptime.
Subareas and Courses
- Database Systems
- Distributed High-Performance Architectures
- Cloud Computing
- Resilient Redundant Data
- Machine Learning Engineering
- Sensor Networks