Data Science Lab

Data Science LabThe Data Science Lab (or DataLab) provides fully dedicated high-speed computational resources in support of the Institute’s analytics educational programs, and for doctoral research in selected areas of computer science focused on big data. The Master of Science in Analytics currently conducts up to seventeen sponsored practicum projects each year. Our practicum teams work on challenging problems with data requirements typically scaling between 0.5 and 2.0 terabytes. Due to data security and governance requirements, the Institute maintains its own computing infrastructure.

The Institute’s computational resources continually evolve to meet the growing needs of projects being conducted by our students. Resources currently operational and in development are shown below. The Institute is in the process of deploying a major new equipment acquisition that will give students access to the latest suite tools in SAS High Performance Analytics (HPA). The HPA architecture implements distributed in-memory processing that provides for extremely fast processing of large data models.


COMPUTATIONAL RESOURCES
Processor
Cores
RAM
(GB)
Raw Storage
(TB)
Usable Storage
(TB)
Operational
136
544
56.5
56.5
Development
672
4032
315.0
300.0
Total Resources
808
4576
371.5
356.5

Current Doctoral Students:

  • Mark Cusick – Machine Learning
  • Andrea Villanes – Text Mining