Data analytics require a considerable amount of data, which must be complete and consistent to obtain meaningful insights. Incomplete data can lead to inaccurate or incomplete results, which can adversely impact the audit's effectiveness. For instance, if an auditor is analyzing sales data to determine if the sales team is meeting its targets, incomplete data may lead to incorrect conclusions.
"Data is from the previous reporting period" - may not be ideal but is not the most significant concern. In some cases, analyzing data from the previous period can be helpful in identifying trends or patterns.
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