Too Big to Ignore: Lato Sensu Business Students’ Perceptions on an Accounting Big Data Case

Vitor Hideo Nasu, Daniel Ramos Nogueira, Elvis Araujo Albertin, Claudio Marques


The objective of this study was to analyze the perceptions of lato sensu business students on an accounting big data case. The case was developed by Hoelscher and Mortimer (2018) and was designed to be used with the Tableau software. It was implemented in two distinct accounting courses from two higher education institutions located in the South region of Brazil. Right after the end of the case’s development, surveys were administered to collect data from the 41 participants. Survey questions were divided into three sections: (i) student’s demographic information; (ii) student’s proficiency level in Excel, Tableau, and Statistical software packages; and (iii) ten case-related and Tableau-related questions that were extracted from prior literature. According to the descriptive statistics, most of the students had low proficiency levels in Tableau before the case’s implementation. After the case, students’ perceptions changed from “none” to “basic” regarding their proficiency level. Also, students found the case interesting, engaging, and useful. It helped them to gain an understanding of how data analytics can be used to answer crucial business questions. Results from the association tests indicated that the students’ demographic and academic information is not significantly associated with the case-related and Tableau-related questions. It means that students who majored in accounting and non-accounting areas had similar perceptions. Then, the case has shown to be a productive activity even for those whose academic background is not directly related to the accounting field. Finally, students’ comments reinforced the positive experience with the case.


Big Data; Educational Case; Business Students; Accounting Education; Survey.

Full Text:



Alles, M., & Gray, G. L. (2016). Incorporating big data in audits: Identifying inhibitors and a research agenda to address those inhibitors. International Journal of Accounting Information Systems, 22, 44–59.

Beaver, D., Kumar, S., Li, H. C., Sobel, J., & Vajgel, P. (2010). Finding a needle in Haystack: Facebook’ s photo storage. Proceedings of the 9th USENIX Symposium on Operating Systems Design and Implementation (OSDI’10), (October), 1–8. Retrieved from

Bello-Orgaz, G., Jung, J. J., & Camacho, D. (2016). Social big data: Recent achievements and new challenges. Information Fusion, 28, 45–59.

Blazquez, D., & Domenech, J. (2018). Big Data sources and methods for social and economic analyses. Technological Forecasting and Social Change, 130(September 2017), 99–113.

Brown-Liburd, H., & Vasarhelyi, M. A. (2015). Big Data and Audit Evidence. Journal of Emerging Technologies in Accounting, 12(1), 1–16.

Cao, M., Chychyla, R., & Stewart, T. (2015). Big Data Analytics in Financial Statement Audits. Accounting Horizons, 29(2), 423–429.

Coyne, E. M., Coyne, J. G., & Walker, K. B. (2018). Big Data information governance by accountants. International Journal of Accounting & Information Management, 26(1), 153–170.

Earley, C. E. (2015). Data analytics in auditing: Opportunities and challenges. Business Horizons, 58(5), 493–500.

Gandomi, A., & Haider, M. (2015). Beyond the hype: Big data concepts, methods, and analytics. International Journal of Information Management, 35(2), 137–144.

Günther, W. A., Rezazade Mehrizi, M. H., Huysman, M., & Feldberg, F. (2017). Debating big data: A literature review on realizing value from big data. The Journal of Strategic Information Systems, 26(3), 191–209.

Hoelscher, J., & Mortimer, A. (2018). Using Tableau to visualize data and drive decision-making. Journal of Accounting Education, 44(October 2017), 49–59.

Igou, A., & Coe, M. (2016). Vistabeans coffee shop data analytics teaching case. Journal of Accounting Education, 36, 75–86.

Janvrin, D. J., Raschke, R. L., & Dilla, W. N. (2014). Making sense of complex data using interactive data visualization. Journal of Accounting Education, 32(4), 31–48.

Janvrin, D. J., & Watson, M. W. (2017). “Big Data”: A new twist to accounting. Journal of Accounting Education, 38, 3–8.

Kokina, J., Pachamanova, D., & Corbett, A. (2017). The role of data visualization and analytics in performance management: Guiding entrepreneurial growth decisions. Journal of Accounting Education, 38, 50–62.

Krahel, J. P., & Titera, W. R. (2015). Consequences of Big Data and Formalization on Accounting and Auditing Standards. Accounting Horizons, 29(2), 409–422.

Laney, D. (2001). 3D data management: Controlling data volume, velocity and variety. META Group Research Note, 6(70), 1. Retrieved from

Lindell, J. (2018). Analytics and Big Data for Accountants. New York, NY: American Institute of Certified Public Accountants, Inc.

Pathways Commission. (2012). The Pathways Commission: Charting a national strategy for the next generation of accountants. Retrieved from

Pincus, K. V., Stout, D. E., Sorensen, J. E., Stocks, K. D., & Lawson, R. A. (2017). Forces for change in higher education and implications for the accounting academy. Journal of Accounting Education, 40, 1–18.

Richins, G., Stapleton, A., Stratopoulos, T. C., & Wong, C. (2017). Big Data Analytics: Opportunity or Threat for the Accounting Profession? Journal of Information Systems, 31(3), 63–79.

Vasarhelyi, M. A., Kogan, A., & Tuttle, B. M. (2015). Big Data in Accounting: An Overview. Accounting Horizons, 29(2), 381–396.

Wamba, S. F., Gunasekaran, A., Akter, S., Ren, S. J., Dubey, R., & Childe, S. J. (2017). Big data analytics and firm performance: Effects of dynamic capabilities. Journal of Business Research, 70, 356–365.

Warren, J. D., Moffitt, K. C., & Byrnes, P. (2015). How Big Data Will Change Accounting. Accounting Horizons, 29(2), 397–407.

Yoon, K., Hoogduin, L., & Zhang, L. (2015). Big Data as Complementary Audit Evidence. Accounting Horizons, 29(2), 431–438.

Zhang, J., Yang, X., & Appelbaum, D. (2015). Toward Effective Big Data Analysis in Continuous Auditing. Accounting Horizons, 29(2), 469–476.


Article Metrics

Metrics Loading ...

Metrics powered by PLOS ALM

Copyright (c) 2019 Future Studies Research Journal: Trends and Strategies

Future Stud. Res. J. e-ISSN: 2175-5825

Mailing Address: Avenida Drª Ruth Cardoso, 7221 - CEP 05425-070 - Pinheiros - São Paulo/SP - Brasil

The publications of this journal are licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.