Business Analytics Major (B.Com.) (72 credits)
Offered by: Management (Desautels Faculty of Management)
Degree: Bachelor of Commerce
Program credit weight: 72
Program Description
The Major in Business Analytics offers an interdisciplinary approach to study the evolving field of management analytics with a strong emphasis on experiential learning. The major is designed to address the growing needs of organizations for business analytics, data science, and artificial intelligence. The emphasis of the program will be on managerial issues and use of state-of-the-art data analytics tools to optimize organizational decisions in a variety of managerial settings.
Note: For information about Fall 2025 and Winter 2026 course offerings, please check back on May 8, 2025. Until then, the "Terms offered" field will appear blank for most courses while the class schedule is being finalized.
Required Courses (54 credits)
Management Core
| Course | Title | Credits |
|---|---|---|
| MGCR 211 | Introduction to Financial Accounting. | 3 |
Introduction to Financial Accounting. Terms offered: Summer 2025 The role of financial accounting in the reporting of the financial performance of a business. The principles, components and uses of financial accounting and reporting from a user's perspective, including the recording of accounting transactions and events, the examination of the elements of financial statements, the preparation of financial statements and the analysis of financial results. | ||
| MGCR 222 | Introduction to Organizational Behaviour. | 3 |
Introduction to Organizational Behaviour. Terms offered: Summer 2025 Individual motivation and communication style; group dynamics as related to problem solving and decision making, leadership style, work structuring and the larger environment. Interdependence of individual, group and organization task and structure. | ||
| MGCR 233 | Data Programming for Business. | 3 |
Data Programming for Business. Terms offered: Summer 2025 Introduction to data programming for management students. | ||
| MGCR 250 | Expressive Analysis for Management. | 3 |
Expressive Analysis for Management. Terms offered: this course is not currently offered. Focusing on skills with respect to analysis, writing and presentation in management. | ||
| MGCR 271 | Business Statistics. | 3 |
Business Statistics. Terms offered: this course is not currently offered. Statistical concepts and methodology, their application to managerial decision-making, real-life data, problem-solving and spreadsheet modeling. Topics include: descriptive statistics; normal distributions, sampling distributions and estimation, hypothesis testing for one and two populations, goodness of fit, analysis of variance, simple and multiple regression. | ||
| MGCR 293 | Managerial Economics. | 3 |
Managerial Economics. Terms offered: Summer 2025 The course focuses on the application of economic theory to management problems and the economic foundations of marketing, finance, and production. Attention is given to the following topics: price and cost analysis; demand and supply analysis, conditions of competition. | ||
| MGCR 294 | The Firm in the Macroeconomy. | 3 |
The Firm in the Macroeconomy. Terms offered: Summer 2025 Topics and tools of macroeconomics such as national accounting, the IS-LM model, the drivers of output and business cycles, and the basics of monetary policy and inflation. Emphasis on financial markets, the role of expectations, and the reasons for possible deviations from full information market efficiency. | ||
| MGCR 331 | Information Technology Management . | 3 |
Information Technology Management . Terms offered: Summer 2025 Introduction to principles and concepts of information systems in organizations. Topics include information technology, transaction processing systems, decision support systems, database and systems development. Students are required to have background preparation on basic micro computer skills including spreadsheet and word-processing. | ||
| MGCR 341 | Introduction to Finance. | 3 |
Introduction to Finance. Terms offered: Summer 2025 An introduction to the principles, issues, and institutions of Finance. Topics include valuation, risk, capital investment, financial structure, cost of capital, working capital management, financial markets, and securities. | ||
| MGCR 352 | Principles of Marketing. | 3 |
Principles of Marketing. Terms offered: Summer 2025 Introduction to marketing principles, focusing on problem solving and decision making. Topics include: the marketing concept; marketing strategies; buyer behaviour; Canadian demographics; internal and external constraints; product; promotion; distribution; price. Lectures, text material and case studies. | ||
| MGCR 372 | Operations Management. | 3 |
Operations Management. Terms offered: Summer 2025 Design, planning, establishment, control, and improvement of the activities/processes that create a firm's final products and/or services. The interaction of operations with other business areas will also be discussed. Topics include forecasting, product and process design, waiting lines, capacity planning, inventory management and total quality management. | ||
| MGCR 382 | International Business. | 3 |
International Business. Terms offered: this course is not currently offered. An introduction to the world of international business. Economic foundations of international trade and investment. The international trade, finance, and regulatory frameworks. Relations between international companies and nation-states, including costs and benefits of foreign investment and alternative controls and responses. Effects of local environmental characteristics on the operations of multi-national enterprises. | ||
| MGCR 423 | Strategic Management. | 3 |
Strategic Management. Terms offered: Summer 2025 An integrative and interdisciplinary introduction to strategy formation and execution. Concepts, tools, and practical application to understand how firms leverage resources and capabilities to gain competitive advantage in dynamic, contemporary industries. Strategic positioning, organizational design, and managerial action for the long-term success of businesses and positive social and ecological outcomes. | ||
| MGCR 460 | Social Context of Business. | 3 |
Social Context of Business. Terms offered: Summer 2025 Examination of how business interacts with the larger society. Exploration of the development of modern capitalist society, and the dilemmas that organizations face in acting in a socially responsible manner. Examination of these issues with reference to sustainable development, business ethics, globalization and developing countries, and political activity. | ||
Major
| Course | Title | Credits |
|---|---|---|
| INSY 336 | Data Handling and Coding for Analytics. | 3 |
Data Handling and Coding for Analytics. Terms offered: this course is not currently offered. Preparation and analysis of data for business analytics. Topics include: data acquisition, data manipulation and computer programming for statistical analysis. | ||
| INSY 446 | Data Mining for Business Analytics. | 3 |
Data Mining for Business Analytics. Terms offered: this course is not currently offered. Practical methods and techniques for data mining and predictive analytics to solve business problems. Use of statistical tools for hands-on learning. Topics covered include supervised learning, unsupervised learning, and text mining. | ||
| MGSC 404 | Foundations of Decision Analytics. | 3 |
Foundations of Decision Analytics. Terms offered: this course is not currently offered. This course teaches quantitative methods used in business decision making. Topics include: optimization models, decision trees, simulation, and computer simulation. Business applications of these techniques are emphasized. Students in this course will acquire expertise in computer based methods for decision making, through computer analysis of real-life problems. | ||
3 credits of experiential learning from the following:
| Course | Title | Credits |
|---|---|---|
| MGSC 483 | Analytics-Based Community Project. | 3 |
Analytics-Based Community Project. Terms offered: Summer 2025 Aiding a host community organization in the application of analytics, with the aim of helping to improve the community's operations for the good of society. | ||
| RETL 407 | Retail Management Project. | 3 |
Retail Management Project. Terms offered: this course is not currently offered. A team-based, experiential project that involves defining actual problems and recommending solutions in the realm of an organization, or at the interface of different organizations (e.g. supply chains), including strategic and operational issues in retail management. Each project is multidisciplinary or multi-functional in nature and will have significant impact on one or more operational/competitive capabilities of the organization. | ||
Complementary Courses (18 credits)
3-6 credits from the following:
| Course | Title | Credits |
|---|---|---|
| MGSC 401 | Statistical Foundations of Data Analytics. | 3 |
Statistical Foundations of Data Analytics. Terms offered: this course is not currently offered. This course will provide statistical foundations for data analytics. In this course, we will learn an introduction to advanced statistical techniques and methodologies including sampling, regression, time-series and multi-variate statistics. We will support our approach by looking at applied examples and real cases and datasets across several business areas, including marketing, human resources, finance, and operations. Students will apply their skills to interpret a real-world data set and make appropriate business recommendations. | ||
| MGSC 416 | Data-Driven Models for Operations Analytics. | 3 |
Data-Driven Models for Operations Analytics. Terms offered: this course is not currently offered. Examination of how data-driven models have been used to transform businesses and industries, using examples and case studies in e-commerce, retail, social and online networks, sports analytics, and online advertising. Demonstration of the use of data-driven analytics methods such as time series forecasting, network models, mixed-integer optimization, matching markets and exploration/exploitation. | ||
6-9 credits of technical component from the following:
| Course | Title | Credits |
|---|---|---|
| INSY 437 | Managing Data and Databases. | 3 |
Managing Data and Databases. Terms offered: this course is not currently offered. Management of organizational data, implementation of database management systems, and the roles and responsibilities of data management personnel. Explores different models of data representation with an emphasis on the relational model; simple and complex SQL queries. | ||
| INSY 442 | Data Analysis and Visualization. | 3 |
Data Analysis and Visualization. Terms offered: this course is not currently offered. Overview of methods and tools for analyzing business data to improve business decision-making, focusing on data visualization using hands-on learning. | ||
| INSY 463 | Deep Learning for Business Analytics. | 3 |
Deep Learning for Business Analytics. Terms offered: this course is not currently offered. Theory of Neural Networks and its applications for business analytics, including how to build and train Neural Networks to derive insights from unstructured text and image data in business contexts. Introduction to the ecosystem of software packages needed in Python, including: NumPy, Pandas, Sklearn. The theory and implementation of Neural Networks and Deep Learning. How to apply various deep learning models to real-world problems and demonstration of their power in the new data-abundant business world. | ||
3-9 credits from the following:
| Course | Title | Credits |
|---|---|---|
| ACCT 451 | Data Analytics in Capital Market. | 3 |
Data Analytics in Capital Market. Terms offered: this course is not currently offered. Exploration of how financial and non-financial metrics can be linked to business performance through experiential learning, with a focus on financial statement analysis, earnings and return predictability, textural analysis, earnings management and fraud detection. Introduction to SAS software and financial accounting databases such as CRSP, Compustat, and I/B/E/S, and alternative data sources such as SEC Edgar that enables work across different database to make better financial statement analysis and decisions. | ||
| BUSA 471 | Artificial Intelligence Ethics for Business. | 3 |
Artificial Intelligence Ethics for Business. Terms offered: this course is not currently offered. Frameworks to highlight model explainability, data anonymity and privacy, bias and fairness. Analytical tools that will allow managers to incorporate these ethical concerns during artificial intelligence development and deployment. | ||
| FINE 460 | Financial Analytics. | 3 |
Financial Analytics. Terms offered: this course is not currently offered. An extensive study of the empirical methods casually used in the different subfields of finance. Examination of the most popular statistics models used in finance, both from a theoretical and practical point of view. An important emphasis will be put on the distinction between models of financial mechanisms, and those motivated purely by efficacy. | ||
| INSY 448 | Text and Social Media Analytics. | 3 |
Text and Social Media Analytics. Terms offered: this course is not currently offered. The unlimited opportunities that exist today to leverage the power of user generated content analytics, focusing on questions ranging from strategic to operational matters pertaining to a firm’s social media initiatives, metrics to capture relevant outcomes, and predictive analysis to link social media chatter to business performance. | ||
| MRKT 440 | Marketing Analytics. | 3 |
Marketing Analytics. Terms offered: this course is not currently offered. Analytic techniques available to marketing managers including practice with actual data sets to use the techniques. Topics covered will include customer and product analytic models, digital marketing, and marketing resource allocation. | ||
| MRKT 442 | Customer Analytics. | 3 |
Customer Analytics. Terms offered: this course is not currently offered. Identification of common data science solutions to customer analytics. What, when, where and how to collect customer data. Basic customer analysis and assessment of the influence of marketing programs on business performance and customer satisfaction. Insights gained from analytics to a non-technical audience. Examination of the cutting edge applications of customer analytics and emerging trends. | ||
| ORGB 330 | People Analytics. | 3 |
People Analytics. Terms offered: this course is not currently offered. This is the era of big data. Companies and organizations are collecting an enormous amount of information and we are only just beginning to grasp the ways in which this information might be used. This course covers the emerging field of people analytics, which involves applying data collection and analysis techniques to improve the management of people within organizations. We will cover current people analytics techniques, common pitfalls, and possible shortcomings of people analytics, as well as the ethical questions involved in undertaking such analyses. | ||
Or any related undergraduate topics course (with approvals from the Business Analytics area and the B.Com. Office).