MGA 312LEC - Introduction to Data Analytics for Accountants

In today’s fast-paced digital world, analytic professionals with the skills to transform data into the kind of actionable intelligence that can drive business decisions are in high demand. Organizations across different business sectors are using data, whether to improve the efficiency of their operations, for more strategic purposes, or even as the basis of their business model. A management accountant is ideally positioned to help an organization focus on gaining insight from data. Therefore, it is important for management accounting students to expand their horizons to include data analytics. Introduction to Data Analytics for Accountants provides students with an overview of instruments and tools utilized in the field to understand, model and make practical use of the very large quantity of data that most businesses are currently collecting. By definition, data analytics is the science of analyzing data to convert information to useful knowledge. This knowledge can help us understand and enable us to make better business decisions. The last 20 years has seen steeply decreasing costs to gather, store, and process data, creating an even stronger motivation for the use of evidence-based approaches to problem solving. This course seeks to present a wide range of data analytic tools and techniques including Excel, Alteryx Designer, and Tableau Desktop and is structured around the broad contours of the different types of data analytics, namely, descriptive, inferential, predictive, and prescriptive analytics. When management accountants combine their accounting and data analysis skills with an understanding of the business, they gain professional credibility and a seat at the decision-making table as trusted providers of management information.

Credits: 3

Grading
Graded (GRD)

Typically Offered:
Spring

Requisites:
Pre-Requisites: MGA 301 and MGA 311 with minimum grades of C in each; concurrent registration in MGA 302; junior standing in Accounting Program.