Management Information Systems Commons^™

Detecting Dirty Data Using Sql: Rigorous House Insurance Case, Daniel Street, James G. Lawson

Faculty Journal Articles

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 …