Explore how the Anomaly Detector service evaluates real-time data for irregularities. Learn about its machine learning-based approach to detecting anomalies in streaming data!
Table of Contents
Question
How does the Anomaly Detector service evaluate real-time data for anomalies?
Answer
It evaluates the current value against the previous value.
Explanation
The Anomaly Detector service evaluates real-time data by utilizing statistical algorithms to establish a baseline behavior pattern from historical data. It compares incoming data points to this pattern, identifying deviations that fall outside the expected range. Leveraging machine learning techniques, the service discerns anomalies based on the likelihood of the observed data being part of the established pattern, enabling it to detect irregularities or outliers in real-time data streams.
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