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Classroom session

Classroom Session 

Wednesday, 11 May – 15:30-17:00 Room C-314 (Boardroom) at NHH (3rd floor of the main NHH building). It may be reached by elevator or stairs.

“Integrating Data Analytics into Your Accounting Courses Using Power BI” PRE-WORKSHOP INSTRUCTIONS

Accountants provide information for decision making. Data analytics that support data driven decisions has become an integral part of what accountants do. Data analytics projects require an integrated skill set:

  • Data preparation. Integrating data from multiple sources, cleaning and transform these data, and restructuring them to make analytics easy.
  • Information modeling. Building formulas to convert these data into the information needed for analytical purposes.
  • Data exploration. Sorting and filtering the data and information in many ways to find insights that can impact a business’ decision-making.

Accounting students that are able to prepare data, build information models, explore data, and interpret and communicate insights are in high demand.

This hands-on classroom session presents an integrated case that requires students to go through the different phases of a data analytics project: from data to insights. The software used for the integrated case is Microsoft Power BI, a business intelligence/data analytics tool developed with Excel users in mind. The session has three parts, each taking about thirty minutes. For each part, we will do some hands-on exercises, discuss the importance of the skills learned, and discuss how to integrate such skills into the accounting curriculum.

Data Preparation. Using Power BI’s ETL tool, Power Query, we will extract data and do some basic data preparation exercises such as unpivoting a table. We will briefly discuss data preparation issues important for accounting students to learn such as incorrect, inconsistent, invalid, and incomplete data.

Information Modeling. Using Power BI’s Data Analysis eXpressions (DAX) language, we will create a simple information model. We briefly discuss the importance of information modeling for data analytics projects: the richer the information model, the richer the analytics. Concepts such as Key Performance Indicators (KPIs) will be linked to information modeling.

Data Exploration. Data exploration is the discovery process of looking for something new and previously unknown. It involves looking for patterns, outliers, or, more generally, for insights. An insight is an observation that might significantly affect a business’ decision-making. We will illustrate how Power BI makes it easy to explore different data relationships (e.g., time series) for insights using visualizations (e.g., a line chart). We will briefly discuss how data exploration can be integrated into the accounting curriculum.

The overall goal of these exercises is to create a data-driven mindset: understanding the difference between good and bad data, how data should be structured for analytical purposes, the difference between data and information, what questions can be answered from a given data set, what data relationships can be investigated, what insights can be provided by the different data relationships, how can insights be visualized, how to interpret insights, and so much more.  Part of our discussion will focus on possible pedagogies to create such a data-driven mindset.


Guido L. Geerts is a professor of accounting and EY Faculty Scholar at the Lerner College of Business, University of Delaware, where he teaches accounting information systems and data analytics. He received a Ph.D. in accounting information systems from the Free University of Brussels, Belgium in 1993. Guido has published more than twenty articles in accounting and information systems journals. He has received numerous teaching, research, and service awards, including the 2015 University of Delaware’s Excellence in Teaching Award and the 2018 American Accounting Association Outstanding Service Award. Guido is the former chair of the Technology Task Force for the Pathways Commission Recommendation 4 (Curriculum and Pedagogy) and currently serves as a Trustee on the AICPA Foundation Board.

Gail Hoover King is a visiting professor for the School of Business at Washburn University where she created and teaches the Foundations of Data Analysis course and helped develop a major, minor and certificate program in Business Data Analytics.  She received bachelors and masters in accounting from the University of Kansas and her doctorate from the University of Northern Illinois School of Business .  Her research focuses on learning, assessment and curriculum.  She has received numerous teaching and service awards, including the 2017 Jim Bulloch Award for Innovations in Management Accounting Education sponsored by the IMA, 2017 Mark Chain Innovation in Graduate Teaching Award from the AICPA/Federation of Schools of Accountancy, and 2016 Bea Sanders/AICPA Innovation in Teaching Award Honorable Mention.  She has been recognized for her service to the American Accounting Association receiving the 2014 American Accounting Outstanding Service award and the 2019 Hall of Honors Award from the Teaching Learning and Curriculum Section.