Big Data Lab

The Big Data Lab is a state-of-the-art facility that combines a computer lab and on-premise data center. Built through a New York state grant of $1 million, it is the University's most powerful academic computing facility.


The Big Data Lab consists of an advanced computer laboratory and data center for hosting academic workloads and services. The computer lab features 20 high-end dual-boot workstations with CentOS Linux and Windows 10. The data center’s portfolio includes 27 servers and storage arrays interconnected by 10 Gbit/sec copper and fiber networking. The data center houses the lab’s high performance VMware cluster and also serves as space for colocation of faculty and departmental servers. The VMware cluster runs on VMware vSphere, a virtualization platform that provides cloud computing infrastructure for running virtual machines (VMs) in a large scale computing environment. The cluster is used for lab assignments, research, storing data, and running CPU intensive calculations. The lab houses a Mac mini cluster to provide an environment with Xcode for iOS development. Students can remotly access the lab’s services and virtual environment through the department’s VPN.


Although any Computer Science class is welcome to use these facilities, the lab is most frequently used for Software Engineering (CSC 190), Operating Systems (CSC 112), Web Application Development (CSC 183/283), Senior Design projects, and special topic classes such as Ethical hacking (CSC 115/215), The Semantic Web (CSC 150/250), etc.

The following courses are offered in or utilize the Big Data Lab:

  • CSC 156/272 - Machine Learning
  • CSC 115/215 - Ethical Hacking
  • CSC 183/283 - Web Application Development
  • CSC 155/290Z - Systems Programming
  • CSC 188/288 - Network Security
  • CSC 290X - Data Science
  • CSC 150/250 - The Semantic Web
  • CSC 145R/291B - Cloud Computing for Big Data
  • CSC 175/284 - Networking & Distributed Processing
  • CSC 273 - Data Mining
  • CSC 125/259 - Concurrent & Parallel Programming

See also