Research is Our Business

The goal of the NSERC Business Intelligence Network is to create an innovation platform for pre-competitive research in Business Intelligence in Canada. NSERC BIN aims to enhance Canadian business competitiveness through the development of intelligent data management and decision-making solutions. Business Intelligence has to move from the silos of finance, accounting, marketing, customer care and inventory management to become an integral part of business operations, driving business decisions using information sources across the entire corporation. Complex organizations are in need of knowledge-management solutions that are more comprehensive than the existing patchwork of data and content management systems currently available. There is a critical need for a business knowledge management architecture where corporate objectives, processes, metadata, and data are linked through organizational and operational objectives.

The NSERC BIN research team consists of 15 investigators at seven universities (University of Alberta, University of British Columbia, Carleton University, Dalhousie University, University of Ottawa, University of Toronto, and University of Waterloo). Investigators are working in partnership with researchers at a number of organizations including SAP Canada Inc., IBM Canada Limited, iAnywhere Solutions Canada Ltd., Palomino System Innovations Inc. and Zerofootprint.

Model-based BI Design Using BIM

On-going reviews of hospital operations throughout Ontario suggest that patients stay in hospital longer than medically necessary. This project applies a range of Business Intelligence (BI) techniques to identify bottlenecks within and beyond the hospital (eg. long-term care facilities, home care services, etc.) that affect hospital patient flow.

Continued

Michael Lawrence

Michael is  PhD Candidate in the Department of Computer Science at the University of British Columbia. His theseis work focuses on coordinating updates between autonomous, heterogeneous databases that are related so that one depends on the other.

Learn more