Accountants regularly work with large amounts of financial and non-financial data. Data modelling is an important means through which accountants can analyse such data for trends, patterns, relationships, and other useful information for decision making. This course will introduce a variety of quantitative techniques used in the development, implementation, and utilization of analytical data models that
accountants regularly use in decision making. It will cover techniques including regression analysis, trend analysis, optimization, text analytics, and simulation.
Visualization provides an important means through which accountants can communicate insights obtained via data modelling to their intended recipients. Well-designed visualisations can improve the memory, comprehension, and decision making of intended recipients of this information. This course will introduce students to key principles and techniques for data visualization. Students will create visuals including dashboards and interactive visualisations for decision making in the accounting context.
Standard Learning Outcomes (for SOA only)
LO1.1: Our students can recognize, develop, measure, record, validate and communicate financial and other related information
LO1.2: Our students can analyze, synthesize and evaluate financial and other related information for decision making in a management context
LO1.3: Our students understand and can apply concepts relating to business processes, audit and assurance
LO2.2: Our students can communicate effectively in a business context.
