Which three actions are used when performing diagnostic analytics?

Question

Options

• AIdentify data anomalies
• BIdentify data anomalies
• CApply serf-learning loops to draw inferences from anomalies.
• DIdentify data anomalies

• A
  81% (29)
• B
  11% (4)
• C
  3% (1)
• D
  6% (2)

Explanation

Identifying data anomalies (A) is a foundational step in diagnostic analytics because the entire process begins with spotting irregularities - deviations from expected patterns - that warrant investigation into why something occurred, which is the defining purpose of diagnostic analytics.

Options B and D are distractors only in their labeling - they are word-for-word identical to A, making them redundant duplicates rather than distinct actions. This appears to be a poorly formatted question where the other two correct choices were accidentally replaced with copies of option A. In a well-formed version of this question, the three actions would typically be: identify anomalies, gather related data to drill down, and determine the root cause.

Option C is incorrect because "self-learning loops to draw inferences" describes machine learning / AI-driven analytics, not diagnostic analytics. Diagnostic analytics relies on structured querying, drill-down, and root-cause analysis - not autonomous model training.

Memory tip: Think of diagnostic analytics as the "Why did this happen?" layer - it goes deeper than descriptive analytics ("What happened?") by using anomaly detection and root-cause investigation, not self-learning algorithms (that's predictive/prescriptive territory).

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