The rapid development of computer and Internet technology has brought human society into the era of information technology, and it has a profound impact on human’s past work, production, management and consumption methods (AICPA, 2014). Even the social economic structure has changed in this general environment. With the rapid development of information technology, tradition has been unable to meet current needs. By combining the concept of big data and the characteristics of audit work in the era of big data, this article explores the effective countermeasures for optimizing the data analysis in the era of big data (Richins et al., 2017).
References
[1]
Adrianto, Z. (2018). Auditing in the Era of Big Data: A Literature Review. Jurnal Akuntansi dan Keuangan, 17, 7-12.
[2]
AICPA (2014). Reimagining Auditing in a Wired World (White Paper). Now York: American Institute of Certified Public Accountants.
[3]
Appelbaum, D., Kogan, A., & Vasarhelyi, M. A. (2017). Big Data and Analytics in the Modern Audit Engagement: Research Needs. Auditing: A Journal of Practice & Theory, 36, 1-27. https://doi.org/10.2308/ajpt-51684
[4]
Byström, H. (2019). Blockchains, Real-Time Accounting, and the Future of Credit Risk Modeling. Ledger, 4, 40-47. https://doi.org/10.5195/ledger.2019.100
[5]
Chen, W., & Smieliauskas, W. (2017). Electronic Auditing Method Based on Data Visualization Technology in Big Data Environment. Chinese Certified Public Accountant, No. 1, 101-106.
[6]
Chen, W., Liu, S. F., Smieliauskas, W. et al. (2012). Influence Factors Analysis of Online Auditing Performance Assessment: A Combined Use between AHP and GIA. Kybernetes, 41, 587-598. https://doi.org/10.1108/03684921211243257
[7]
Clatworthy, M., García Lara, J. M., & Lee, E. (2020). 50 Years of Accounting and Business Research. Accounting and Business Research, 50, 1-5. https://doi.org/10.1080/00014788.2020.1690742
[8]
Gepp, A., Linnenluecke, M. K., O’Neill, T. J., & Smith, T. (2018). Big Data Techniques in Auditing Research and Practice: Current Trends and Future Opportunities. Journal of Accounting Literature, 40, 102-115. https://doi.org/10.1016/j.acclit.2017.05.003
[9]
Ho-Quang, T., Chaudron, M. R., Hebig, R., & Robles, G. (2020). Challenges and Directions for a Community Infrastructure for Big Data-Driven Research in Software Architecture. In Model Management and Analytics for Large Scale Systems (pp. 13-35). Cambridge, MA: Academic Press. https://doi.org/10.1016/B978-0-12-816649-9.00010-7
[10]
Ji, X. D. (2017). Development of Accounting and Auditing Systems in China. Abingdon-on-Thames: Routledge. https://doi.org/10.4324/9781315210124
[11]
Kuhn Jr, J. R., & Sutton, S. G. (2010). Continuous Auditing in ERP System Environments: The Current State and Future Directions. Journal of Information Systems, 24, 91-112. https://doi.org/10.2308/jis.2010.24.1.91
[12]
Li, X. L., & Gong, H. G. (2015). Overview of Big Data System. Chinese Science and Information Science, No. 1, 144.
[13]
Luo, J., Meng, Q. and Cai, Y. (2018) Analysis of the Impact of Artificial Intelligence Application on the Development of Accounting Industry. Open Journal of Business and Management, 6, 850-856.
[14]
McKinsey Global Institute (2011).
[15]
Mike 2.0 (2014). Big Data Definition—Mike 2.0.
[16]
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, 63-79. https://doi.org/10.2308/isys-51805
[17]
Sjöberg, P., & Johansson, M. (2016). Shaping the Future of the Auditing Profession in Sweden: A Study of the Expected Role of Digitalization.
[18]
Xu, L. D., & Duan, L. (2019). Big Data for Cyber Physical Systems in Industry 4.0: A Survey. Enterprise Information Systems, 13, 148-169. https://doi.org/10.1080/17517575.2018.1442934
[19]
Zhang, J., Yang, X., & Appelbaum, D. (2015). Toward Effective Big Data Analysis in Continuous Auditing. Accounting Horizons, 29, 469-476. https://doi.org/10.2308/acch-51070
[20]
Zikopoulos, P., & Eaton, C. (2011). Understanding Big Data: Analytics for Enterprise Class Hadoop and Streaming Data. New York: McGraw-Hill Osborne Media.
