Planning to Employ Data Analytics in Audit?

B.

When an IS auditor is planning to use data analytics in an upcoming audit, the greatest concern should be whether the available data is accurate and reliable enough to support the analysis. Therefore, option C - "Available data is incomplete" - is the most critical concern that the IS auditor should have.

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.

Option A - "There is no documented data model" - can be a concern, but it is not the most significant. A documented data model can help an IS auditor understand the structure of the data, but it is not essential to perform data analysis.

Option B - "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.

Option D - "Data fields are used for multiple purposes" - can be a concern, but it is not as significant as incomplete data. If data fields are used for multiple purposes, it can lead to confusion, but an IS auditor can mitigate this risk by understanding how the data is used and ensuring that the analysis is appropriate for the data's purpose.

In conclusion, when an IS auditor is planning to use data analytics in an upcoming audit, the most significant concern should be whether the available data is complete and reliable enough to support the analysis. Therefore, option C - "Available data is incomplete" - is the best answer.