Toward Effective Big Data Analysis in Continuous Auditing
识别了大数据与持续审计数据分析之间的五个差距（数据一致性、完整性、聚合、识别和保密性），并针对每个差距提出挑战和传统数据系统的解决方案。
SYNOPSIS 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.