Understanding memory consumption in a distributed data analytics system

Data analytics has emerged as an important driver for economic success in many businesses and in the public sector. In healthcare, using data analytics promises to reduce costs and improve patient diagnostics and treatment. This project is a collaboration with a Vancouver-based company PHEMI Systems that provides data analytics solutions for healthcare and other industries. Our goal is to understand how to make data analytics system used by PHEMI and many others more efficient in terms of consumed resources while at the same time meeting the needs of privacy.

Faculty Supervisor:

Alexandra Fedorova

Student:

Craig Mustard

Partner:

PHEMI Systems

Discipline:

Engineering - computer / electrical

Sector:

Information and communications technologies

University:

Program:

Accelerate

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