Publication Date
Summer 6-2021
Description
Proficiency with data analytics is an increasingly important skill within in the accounting profession. However, successful data analysis requires clean source data (i.e., source data without errors) in order to draw reliable conclusions. Although users often assume clean source data, this assumption is frequently incorrect. Therefore, identifying and remediating “dirty data” is a prerequisite to effective data analysis. You, an accountant working at a firm that specializes in data analytics, have been hired by Rigorous House Insurance to analyze the company’s claim insurance data. In addition to investigating specific issues mentioned by the company’s controller, you are tasked with identifying any other data integrity issues that you encounter and providing preventative information system internal control suggestions to the client to mitigate these issues in the future.
Journal
Journal of Accounting Education
Volume
55
First Page
100714
Last Page
100725
Department
Accounting and Financial Management
Open Access
Full text attached
Link to Published Version
https://doi.org/10.1016/j.jaccedu.2021.100714
DOI
10.1016/j.jaccedu.2021.100714
Recommended Citation
Street, Daniel and Lawson, James G.. "Detecting Dirty Data Using SQL: Rigorous House Insurance Case." (2021) : 100714-100725.
Included in
Accounting Commons, Management Information Systems Commons, Technology and Innovation Commons