REQUIRED TEXTS/MATERIALS/SOFTWARE/COMPUTER

Textbook: Data Analytics for Accounting, 3rd Edition, By Vernon Richardson and Katie Terrell and Ryan Teeter (McGraw-Hill), ISBN: 9781264444908

Software: We use a variety of different software in this course including Excel, Tableau, Power BI, GoogleSheets, Python, Alteryx, Access, UiPath, and ChatGPT. You will not need to purchase any of this software. Instructions on how to access the software are provided in Blackboard.

Computer: You will need a computer for this course. The computer will need to be able to run the above software. While we will not be working with large data sets, if you have an “older” computer, you may not be able to use your own computer and you will need to use a virtual machine. If you are a MAC user, Power BI, Alteryx, Access and UiPath will not work on your machine unless you use Boot Camp or a virtual machine. Instructions on how to access a virtual machine will be provided in Blackboard. When using the virtual machine, you may experience lag time or connectivity issues.

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, etc. 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. 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. While there will be some use of tools in this course, the focus of this class is on concepts, not software, algorithms or statistical math.

Transferability of workforce courses varies. Students interested in transferring courses to another college should speak with their Area of Study (AoS) advisor, Department Chair, and/or Program Director.

The demand for accountants with data analytics skills is growing rapidly (Vasarhelyi, Tschakert, Kokina, & Kozlowski, 2017). PricewaterhouseCoopers (2015) identified introduction to data visualization software (such as Tableau and PowerBI) as a recommended skill set students need in order to succeed in a rapidly changing business world. Additionally, accrediting body of business and accounting programs expect accounting programs to incorporate learning experiences that develop skills and knowledge related to the integration of information technology and data analytics in accounting and business throughout their curriculum. And finally, both the Certified Public Accountant exam and the Certified Management Accountant exam are including data analytic content and learning objectives. Accounting students who graduate with a solid understanding of data analytics will be sought out by employers.

After successful completion of this course, students will be able to:

• Recognize when and how data analytics can address business questions
• Comprehend the process needed to clean and prepare the data before analysis
• Recognize what is meant by data quality, be it completeness, reliability, or validity
• Perform basic analysis to understand the quality of the underlying data and their ability to address the business question
• Demonstrate ability to sort, rearrange, merge, and reconfigure data in a manner that allows enhanced analysis
• Identify and implement an approach that will use statistical data analysis to draw conclusions and make recommendations on a timely basis
• Report results of analysis in an accessible way to each varied decision maker and their needs

This course includes homework, quizzes, labs, and projects. Refer to the syllabus posted in Blackboard for more detailed information including due dates.