An internal auditor is using data analytics to focus on high-risk areas during an engagement. The auditor has obtained data and is working to eliminate redundancies in the data. Which of the following statements is true regarding this scenario?
A.
The auditor is normalizing data in preparation for analyzing it.
B.
The auditor is analyzing the data in preparation for communicating the results.
C.
The auditor is cleaning the data in preparation for determining which processes may be involved.
D.
The auditor is reviewing the data prior to defining the question.
In data analytics, data cleaning involves identifying and correcting errors, inconsistencies, and redundancies in the dataset to ensure accuracy and reliability. By eliminating duplicate or irrelevant data, the internal auditor enhances the quality of the dataset, which is crucial for accurate analysis and risk assessment. This process is a preparatory step before analyzing the data to identify high-risk areas. Normalization (option A) refers to organizing data to reduce redundancy but is more specific to database design. Analyzing data (option B) and reviewing data prior to defining the question (option D) are steps that occur before and after data cleaning, respectively.
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