What is anomaly detection conceptually?

< 1 min read

Anomaly detection is the process of identifying unusual patterns or data points that deviate from expected behavior.
In one project, we detected an unexpected spike in daily transactions that indicated a system error.
It helps highlight outliers in sales, traffic, or operational metrics.
Anomalies can indicate fraud, data quality issues, or emerging business opportunities.
We compared actual values against historical trends to identify deviations.
Statistical thresholds or machine learning models can automate detection.
As a BA, I use anomaly detection to trigger deeper investigation.
Overall, it helps proactively identify risks or unusual events in business data.

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