Accounting Data Analytics

Catalog description

This course focuses on helping students develop data analytic skills using accounting data. Data has proliferated in business and managers and accountants need to understand the implications for decision-making and tap into the data to provide better insights into a firm/client/customer/supplier. This course is intended to provide students with an understanding of data analytic thinking and terminology as well as hands-on experience with data analytics tools and techniques. It is designed to help accounting students develop an analytical mindset and link data analytics to four major subdomains of accounting (i.e., financial, managerial, audit, and tax). It will cover how to use programming software to automate data analytic tasks. Students will learn how to analyze large amounts of data to find actionable insights. The first half of the course introduces the accounting data analytics framework. Under this framework, students will learn the importance of assembling accounting data, the desirable characteristics of data for effective calculations and visualization, and analysis and interpretation of fundamental data analytic tools, such as regressions. The second half of the course focuses on how to apply data analytic skills to the four major subdomains of accounting: financial, managerial, audit, and tax. Respective hands-on examples will be used for demonstration. Students should leave this course with the skills necessary to translate accounting and business problems into actionable proposals that they can competently present to managers and data scientists.