Accounting with Cognitive Analytics
The master of science in accounting with cognitive analytics develops accounting with data analytics capabilities. With a curriculum integrating advanced accounting techniques, data and visualization skills, statistical and analytical capabilities, and agile teaming skills, accounting industry professionals will learn to contribute and lead analytical teams in organizational projects. Students are challenged in a team environment to demonstrate significant benefits that could accrue from real-world analytic projects in accounting, enabling graduates to excel as participants and business leaders in complex data and analytic projects.
Applicants must satisfy the University admission requirements as stated in Graduate General Regulation 1.3 in the SFU Calendar. An undergraduate degree in business, management, commerce, or other suitable quantitatively oriented programs is required and a minimum of two years of applicable work experience. Candidates holding a professional designation such as a CPA and evidence of strong mathematics competency would also be ideal candidates.
Advanced credit of equivalent courses may be granted from the certificate in accounting with digital analytics.
The master of science in accounting with cognitive analytics consists of course work and an applied project for a minimum of 33 units. Courses from other SFU graduate business programs, or a special topic course, may be substituted at the discretion of the academic director.
Students must complete all of
Enterprise information systems, the relational database systems that underlie them, and creating value through competitive analytics. Develop an understanding of database querying and analytical applications to inspect, summarize, and transform data.
An exploration of financial and non-financial data using summary measures, predictive models for decision-making, and graphic visualizations.
The application of data warehousing solutions to develop an integrated system of policies, applications, and network technologies designed to convert operational data into accessible business information.
Provides an understanding of business intelligence tools beyond the univariate measures addressed in BUS 831. Multivariate modeling approaches are extended to build statistical models relating target behaviour to predictor variables. Prerequisite: BUS 831.
Provides an understanding of forensic accounting and the potential data analytics has in finding fraudulent financial reporting.
and all of the projects
A team-based strategic business analysis and essay supervised by a Simon Fraser University faculty member with support from a senior industry partner. Graded on a satisfactory/unsatisfactory basis.
A team-based strategic business analysis and extended essay supervised by a Simon Fraser University faculty member with support from a senior industry partner. This is the first part of a two part course. Graded on a satisfactory/unsatisfactory basis.
A team-based strategic business analysis and extended essay supervised by a Simon Fraser University faculty member with support from a senior industry partner. The final project will be examined by two readers. This is the second part of a two part course. Graded on a satisfactory/unsatisfactory basis. Prerequisite: BUS 845.
Students are expected to complete the program requirements within five terms.
Advanced credit of equivalent courses may be granted from the certificate in accounting with digital analytics with a final grade of B or higher.
Academic Requirements within the Graduate General Regulations
All graduate students must satisfy the academic requirements that are specified in the Graduate General Regulations, as well as the specific requirements for the program in which they are enrolled.