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Gain a Foundation in Data Analytics

Accounting has always been about analytical thinking. The skillset that accountants needed to perform math and to keep order has evolved from pencil and paper, to typewriters and calculators, then to spreadsheets and accounting software. A new skillset that is becoming more important for nearly every aspect of business is big data analytics: analyzing large amounts of data to find actionable insights. This course is designed to help accounting professionals develop an analytical mindset and prepare them to use data analytic programming languages like Python and R.

Upon successful completion of Beyond the Basics: Data Analytics and Visualization for Accounting Professionals, you will earn a certificate of completion, and a digital badge. In addition, through collaboration with the Institute of Management Accountants you will earn 21.5 ICMA CPE.

Course Overview

Bridging Accountancy to Analytics
We identify how tasks in managerial accounting have historically required an analytical mindset, and we then explore how those tasks can be completed more effectively and efficiently by using big data analytics. We then present a FACT framework for guiding big data analytics: Frame a question, Assemble data, Calculate the data, and Tell others about the results.

Assembling & Visualizing Data
Using financial statement data, we explain desirable characteristics of both data and datasets that will lead to effective calculations and visualizations. We describe visual perception principles and then apply those principles to create effective visualizations. We then examine fundamental data analytic tools, such as regression, linear programming (using Excel Solver), and clustering in the context of point-of-sale data and loan data. We conclude by demonstrating the power of data analytic programming languages to assemble, visualize, and analyze data.

Mastering Data Analytic Tools
We examine fundamental data analytic tools, such as regression, linear programming (using Excel Solver), and clustering in the context of point-of-sale data and loan data. We conclude by demonstrating the power of data analytic programming languages to assemble, visualize, and analyze data. We introduce Visual Basic for Applications as an example of a programming language, and the Visual Basic Editor as an example of an integrated development environment (IDE).

Learning Outcomes

Upon successful completion of this course, you will be able to:

  • Articulate the benefits of using big data and analytics in the modern accounting profession.
  • Describe and implement a framework for using big data to help provide insights that lead to action.
  • Critique the ability of a dataset to answer questions, and then assemble data from different sources into a structure that can be summarized, visualized, and analyzed.
  • Use Excel, Tableau, and Visual Basic for Applications to design and perform basic and advanced analyses.

 

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