Nuriddin Tojiboyev, Deniz Appelbaum, A. Kogan, M. Vasarhelyi
{"title":"Basics of SQL for Audit Data Retrieval and Analysis","authors":"Nuriddin Tojiboyev, Deniz Appelbaum, A. Kogan, M. Vasarhelyi","doi":"10.2308/jeta-2020-021","DOIUrl":null,"url":null,"abstract":"The purpose of this teaching note is to explain how Structured Query Language (SQL) queries can help auditors to independently retrieve properly formatted data as audit evidence or for further analyses. The note demonstrates data extraction using Microsoft (MS) Access, one of the simplest SQL compliant database software applications. We use a dataset fragment extracted from the publicly available enterprise datasets provided by Walton College (University of Arkansas) to run SQL queries as a part of audit investigations. Data extraction is the first step of Extract, Transform, and Load (ETL) and may be time-consuming. We demonstrate how SQL queries can assist with this task, thereby allowing the auditor to begin analysis sooner. This teaching note can be used to prepare future auditors for the emerging data-rich and technology-driven business environment.","PeriodicalId":45427,"journal":{"name":"Journal of Emerging Technologies in Accounting","volume":" ","pages":""},"PeriodicalIF":1.6000,"publicationDate":"2021-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Emerging Technologies in Accounting","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2308/jeta-2020-021","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}
引用次数: 2
Abstract
The purpose of this teaching note is to explain how Structured Query Language (SQL) queries can help auditors to independently retrieve properly formatted data as audit evidence or for further analyses. The note demonstrates data extraction using Microsoft (MS) Access, one of the simplest SQL compliant database software applications. We use a dataset fragment extracted from the publicly available enterprise datasets provided by Walton College (University of Arkansas) to run SQL queries as a part of audit investigations. Data extraction is the first step of Extract, Transform, and Load (ETL) and may be time-consuming. We demonstrate how SQL queries can assist with this task, thereby allowing the auditor to begin analysis sooner. This teaching note can be used to prepare future auditors for the emerging data-rich and technology-driven business environment.