"The science and art of discovering and analyzing patterns, identifying anomalies, and extracting other useful information in data underlying or related to the subject matter of an audit through analysis, modeling, and visualization for the purpose of planning or performing the audit" is the definition of
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Question

"The science and art of discovering and analyzing patterns, identifying anomalies, and extracting other useful information in data underlying or related to the subject matter of an audit through analysis, modeling, and visualization for the purpose of planning or performing the audit" is the definition of 
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BlackTom AI · Accepted Answer

The question presents a formal definition and asks you to identify the term that fits exactly.
Option 1: 'artificial intelligence' – While AI can be used to analyze data, the definition given emphasizes discovering and analyzing patterns, identifying anomalies, and extracting useful information specifically in the context of auditing data. AI is broader and not tailored to the audit data analytics discipline as described.
Option 2: 'robotic processes' – This typically refers to robotic process automation (RPA), which focuses on automating repetitive, rule-based tasks. It does not capture the analytical, pattern-detection, and visualization aspects described in the definition.
Option 3: 'Big Data analysis' – This term highlights handling large datasets and complex analyses, but the definition ties the analysis directly to the subject matter of an audit and to the practice of auditing specifically, whereas 'Big Data analysis' is a more general data-domain concept.
Option 4: 'audit data analytics' – This phrase precisely matches the definition’s scope: it denotes the science and art of discovering and analyzing patterns, identifying anomalies, and extracting useful information in data underlying or related to the subject matter of an audit, accomplished through analysis, modeling, and visualization for planning or performing the audit.
In summary, the fourth option directly reflects the term described in the definition and aligns with the audit-specific context and methods outlined (analysis, modeling, visualization within auditing data).

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