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You are developing a system that will monitor temperature data from a data stream. The system must generate an alert in response to atypical values. The solution must minimize development effort. What should you include in the solution?
Correct Answer: A
The requirement: * You have a system monitoring temperature data from a single data stream. * The system must generate an alert in response to atypical values. * The solution must minimize development effort. Analysis of Options: * Univariate Anomaly Detection * Designed for detecting anomalies in a single time series (e.g., temperature, pressure, humidity, sales). * Since the system monitors temperature only, this is a classic univariate case. * Provides simple integration with minimal effort. * Correct choice. * Azure Stream Analytics * Can process real-time streaming data and detect conditions (with custom queries). * However, it requires more development effort since you would need to manually code logic for anomaly detection. * Not the minimal-effort option. * Metric alerts in Azure Monitor * Used to trigger alerts on predefined thresholds (static rules). * Not intelligent anomaly detection-does not automatically learn patterns from data. * Would require manual threshold setup, which is not efficient for anomaly detection. * Multivariate Anomaly Detection * Used when analyzing multiple related time series (e.g., temperature, pressure, vibration all together). * Since this scenario only has one variable (temperature), multivariate is unnecessary and adds complexity. The Answer: A. Univariate Anomaly Detection * Azure AI Anomaly Detector - Univariate * Multivariate Anomaly Detector * Difference between univariate and multivariate anomaly detection Microsoft References