Why should anomalies in the Large Data Set be identified and explained?

• A. They may reflect unusual events or data errors and can affect interpretation if ignored.
• B. Anomalies should always be ignored.
• C. Anomalies confirm a pattern.
• D. Anomalies are the main focus of data.

Answer: (D)

Anomalies are deviations from what the data would normally show, and recognizing them helps you understand when something unusual is happening or when there might be a data error. If you ignore these deviations, they can distort summaries, mislead interpretations, or hide important information about how the system really behaves. By identifying and explaining anomalies, you can decide whether to correct errors, adjust your analysis to be robust to outliers, or investigate genuine rare events that deserve closer study.

Choosing to ignore anomalies isn’t appropriate because these deviations can skew results, they don’t merely confirm a pattern, and data analysis isn’t about focusing on anomalies alone but about understanding overall patterns and data quality.