What is Anomaly Detection?

Anomaly detection is widely used in finance, healthcare, cybersecurity, and manufacturing for tasks like fraud detection, equipment monitoring, and identifying system failures.

Real-time anomaly detection systems continuously monitor streaming data to identify and flag anomalies instantly, enabling faster response and decision-making.

While all anomalies are outliers, not all outliers are anomalies—anomalies are outliers that indicate unusual or potentially harmful behavior.

Yes, using machine learning algorithms and anomaly detection models, systems can automatically detect and alert on abnormal patterns without human intervention.

Not always—supervised anomaly detection uses labeled data, but unsupervised techniques can detect anomalies without prior labeling.