Business Analytics

The UAlberta MBA with a focus on Business Analytics allows you to complete the same core business courses all MBA students complete, a choice of free electives tailored to your interests, and a focus on the growing field of business analytics. The Business Analytics stream covers data analysis and decision making, predictive analytics, and prescriptive analytics.

Business Analytics Outline

Business Analytics Courses

OM 502: Operations Management
This course focuses on (1) the competitive advantage that a business unit can derive from innovative and efficient production and delivery of its goods and services and on (2) analytical approaches that are useful in understanding and improving an organization's operations. Specific modules include process diagramming and analysis; measuring and managing flow times; inventory control and optimization; supply chain coordination and operations strategy. Cases will be used to illustrate operational efficiency and its significance to the profitability of a firm. Prerequisite: MGTSC 501.
MGTSC 645: Introduction to Business Analytics
The merging of massive data-sets with analytical tools from Statistics, Computer Science, and Operations Research has created the emerging field of analytics. Methods are developing rapidly based on statistical platforms such as SAS and R, or more general purpose programming tools such as Python. This course will build on the basis from MGT SC 501 to provide an overview of Big Data and analytics, and develop programming and methodological skills to acquire, analyze, and present analysis. Prerequisite: MGTSC 501.
OM 620: Predictive Business Analytics
This course provides an introduction to Business Analytics - the combined use of data analysis techniques and optimization models to make data-driven business decisions. Business Analytics has applications in finance, marketing, and operations, such as insurance risk management, credit risk evaluation, targeted advertising, appointment scheduling, hotel and airline overbooking, and fraud detection. Students will learn how to build basic predictive models using data mining software and how to integrate the predictions into spreadsheet simulation models. The emphasis is on the practical use of analytical tools to maximize organizational objectives rather than on algorithm details. Prerequisite: MGTSC 501.
OM 622: Simulation and Computer Modelling Techniques in Management
This course will discuss computer modelling of management systems in such functional areas as accounting, finance, marketing, and production. Basic concepts of deterministic and probabilistic (Monte Carlo) simulation and their applications will also be covered. Micro computer implementations of case studies using spreadsheets will be particularly emphasized. A term project will be required. Prerequisite: MGTSC 502 or OM 502. Not to be taken by students with credit in MGTSC 632.
OM 671: Decision Support Systems
Decision support systems integrated with various management tools in a microcomputer environment. The programming language to be used is Visual Basic for Applications. Different multicriteria decision-making tools such as the Analytic Hierarchy Process, Multiattribute Utility Theory, Goal Programming, and Multiobjective Optimization are introduced. Students create decision support systems with graphical user interfaces that use a formal multicriteria decision-making front end as well as optimization, simulation or other appropriate engines for calculations in the background. Student projects in this implementation-oriented course will come from different areas such as employee scheduling, facility location, project/product selection, and portfolio optimization. Prerequisite: MGTSC 501. Not to be taken by students with credit in MGTSC 671.