Exam AI-102 topic 1 question 45 discussion

A is the answer. https://learn.microsoft.com/en-us/azure/applied-ai-services/metrics-advisor/overview Metrics Advisor is a part of Azure Applied AI Services that uses AI to perform data monitoring and anomaly detection in time series data. The service automates the process of applying models to your data, and provides a set of APIs and a web-based workspace for data ingestion, anomaly detection, and diagnostics - without needing to know machine learning. Developers can build AIOps, predicative maintenance, and business monitor applications on top of the service.

This came in the exam 28/06/2023

Azure AI Anomaly Detector is the optimal choice for this scenario due to its prebuilt models for multi-sensor correlation analysis and low-code implementation. Why Not Other Options? A. Metrics Advisor: Focuses on business metrics (e.g., revenue, web traffic), not IoT sensor data, and is being deprecated. B. Form Recognizer: Extracts text/data from documents, irrelevant for sensor analysis. C. Azure Machine Learning: Requires custom model development, increasing time/resources compared to Anomaly Detector’s prebuilt APIs.

Azure Metrics Advisor was retired on September 20, 2023 and replaced by Azure AI Anomaly Detector. If the Exam is updated, is D

To build an app that performs anomaly detection across multiple correlated sensors, identifies the root cause of process stops, and sends incident alerts while minimizing development time, you should use Azure Metrics Advisor. Azure Metrics Advisor is designed for monitoring and detecting anomalies in time-series data, making it suitable for handling multiple correlated sensors. It also provides root cause analysis and incident alerting capabilities

Azure Metrics Advisor is CORRECT because it is specifically designed for monitoring and detecting anomalies in time-series data from multiple sources. It can handle correlated sensor data, perform root cause analysis, and send incident alerts, all while minimizing development time with its built-in capabilities. A is correct

Should be A, but it is retired. D

A. Azure Metrics Advisor. It’s designed for anomaly detection across multiple data streams, can identify root causes, and send incident alerts—all while minimizing development time

Should be A, But starting on the 20th of September, 2023 you won’t be able to create new Metrics Advisor resources. The Metrics Advisor service is being retired on the 1st of October, 2026. Source: https://learn.microsoft.com/en-us/azure/ai-services/metrics-advisor/overview

To build an app that performs anomaly detection across multiple correlated sensors, identifies the root cause of process stops, and sends incident alerts while minimizing development time, you should use: D. Anomaly Detector The Anomaly Detector service is designed to handle multivariate anomaly detection, which means it can analyze multiple correlated signals and identify anomalies. It also helps in pinpointing the root cause of anomalies and can be integrated with alerting mechanisms to send incident alerts⁵⁶. This service is well-suited for your requirements and minimizes development effort by providing pre-built models and easy integration.

Azure AI Metrics Advisor https://learn.microsoft.com/en-us/azure/ai-services/metrics-advisor/overview

Streaming data Metric Advisor where as batch data Anamoly detector.

A is the answer.

D is Correct for anomaly detection

A is right. From Takedajuku perspective, if you study for 4 days and spend 2 days reviewing, you will have a better chance of passing the exam.

Why is A?

Given the requirements to perform anomaly detection across multiple correlated sensors, identify the root cause of process stops, and send incident alerts while minimizing development time, Azure Machine Learning seems to be the most appropriate choice. So, I'm confident in option: C. Azure Machine Learning.