Toward effective big data analysis in continuous auditing

Juan Zhang, Xiongsheng Yang, Deniz Appelbaum

Research output: Contribution to journalArticle

40 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)469-476
Number of pages8
JournalAccounting Horizons
Volume29
Issue number2
DOIs
StatePublished - 1 Jun 2015

Fingerprint

Continuous auditing
Integrity
Global economy
Confidentiality

Keywords

  • Big data
  • Continuous auditing
  • Gap analysis

Cite this

Zhang, Juan ; Yang, Xiongsheng ; Appelbaum, Deniz. / Toward effective big data analysis in continuous auditing. In: Accounting Horizons. 2015 ; Vol. 29, No. 2. pp. 469-476.
@article{b66346536e0f4688bac77fbf16b9e8ff,
title = "Toward effective big data analysis in continuous auditing",
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.",
keywords = "Big data, Continuous auditing, Gap analysis",
author = "Juan Zhang and Xiongsheng Yang and Deniz Appelbaum",
year = "2015",
month = "6",
day = "1",
doi = "10.2308/acch-51070",
language = "English",
volume = "29",
pages = "469--476",
journal = "Accounting Horizons",
issn = "0888-7993",
publisher = "American Accounting Association",
number = "2",

}

Toward effective big data analysis in continuous auditing. / Zhang, Juan; Yang, Xiongsheng; Appelbaum, Deniz.

In: Accounting Horizons, Vol. 29, No. 2, 01.06.2015, p. 469-476.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Toward effective big data analysis in continuous auditing

AU - Zhang, Juan

AU - Yang, Xiongsheng

AU - Appelbaum, Deniz

PY - 2015/6/1

Y1 - 2015/6/1

N2 - 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.

AB - 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.

KW - Big data

KW - Continuous auditing

KW - Gap analysis

UR - http://www.scopus.com/inward/record.url?scp=84943541255&partnerID=8YFLogxK

U2 - 10.2308/acch-51070

DO - 10.2308/acch-51070

M3 - Article

AN - SCOPUS:84943541255

VL - 29

SP - 469

EP - 476

JO - Accounting Horizons

JF - Accounting Horizons

SN - 0888-7993

IS - 2

ER -