In this new world of audit data analytics, it is important to
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Question

In this new world of audit data analytics, it is important to 
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BlackTom AI · Accepted Answer

In this question, we are prompted to complete the sentence: In this new world of audit data analytics, it is important to 
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Option 1: 'consider the usefulness of the data' — This choice aligns with a fundamental principle in data analytics for auditing: assess whether the data actually provides value for the analysis and decision-making. It emphasizes relevance, quality, and applicability rather than collecting or using data blindly.
Option 2: 'avoid the use of social media' — While social media data can be noisy or unreliable for many audit purposes, outright avoidance is not a universal rule. There are scenarios where social media signals can be informative, provided appropriate validation and context are applied, so this statement is overly restrictive.
Option 3: 'rely only on data sources that are external to the client' — Exclusively external data ignores the rich, internal records that often drive audits, such as transaction logs, control attestations, and internal dashboards. Relying solely on external sources limits the completeness and context of the analysis.
Option 4: 'rely only on data sources that are internal to the client' — Conversely, using only internal data can miss external influences, benchmarks, and market context. Auditing benefits from triangulation with external data alongside internal sources.
Overall, the central idea in modern audit data analytics is to evaluate data for usefulness and fit for purpose, rather than adopting blanket rules about data provenance or sources. This makes option 1 the most reasonable choice, while the others impose unnecessary restrictions or disregard important data opportunities.

In this new world of audit data analytics, it is important to Blank ______.

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