Toward Effective Big Data Analysis in Continuous Auditing
Big Data now pervades every sector and function of the global economy. This paper focuses on the gaps between Big Data and the current capabilities of data analysis in continuous auditing (CA). It identifies four dimensions of Big Data and five subsequent gaps: namely, data consistency, integrity, aggregation, identification, and confidentiality. For each gap, the paper outlines challenges and possible solutions derived from traditional data systems, which can be further applied to CA systems in an era of Big Data.
MSU Digital Commons Citation
Zhang, Juan; Yang, Xiongsheng; and Appelbaum, Deniz, "Toward Effective Big Data Analysis in Continuous Auditing" (2015). Department of Accounting and Finance Faculty Scholarship and Creative Works. 132.