Toward Effective Big Data Analysis in Continuous Auditing

Authors

Juan Zhang, Nanjing University
Xiongsheng Yang, Nanjing University
Deniz Appelbaum, Montclair State UniversityFollow

Document Type

Article

Publication Date

6-1-2015

Journal / Book Title

Accounting Horizons

Abstract

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.

DOI

10.2308/acch-51070

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.
https://digitalcommons.montclair.edu/acctg-finance-facpubs/132

Published Citation

Zhang, J., Yang, X., & Appelbaum, D. (2015). Toward effective big data analysis in continuous auditing. Accounting Horizons, 29(2), 469-476.