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!
How does the Anomaly Detector service evaluate real-time data for anomalies?
It evaluates the current value against the previous value.
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.
Microsoft Azure AI Fundamentals AI-900 certification exam practice question and answer (Q&A) dump with detail explanation and reference available free, helpful to pass the Microsoft Azure AI Fundamentals AI-900 exam and earn Microsoft Azure AI Fundamentals AI-900 certification.