Management and mining of big energy sector data

With advances in techniques, high volumes of valuable data are generated in many domains (e.g., energy sector) at a rapid rate. Consequently, a scalable and flexible system for efficient storage and fast management of these distributed data is needed. In this proposed research project, we plan to design and implement a cloud-based data storage & management system that is flexible, scalable and fast to handle distributed data in a parallel fashion for the partner organization. In addition, we also plan to design and implement a system that conducts parallelized data mining and machine learning to discover new patterns from the data stored in the above data management system. These discovered patterns would be beneficial to the partner organization as these patterns help complex decision making.

Faculty Supervisor:

Carson Leung

Student:

Partner:

Invenia Technical Computing

Discipline:

Computer science

Sector:

Information and cultural industries

University:

University of Manitoba

Program: