You have an Azure IoT hub that receives sensor data from machinery.
You need to build an app that will perform the following actions:
• Perform anomaly detection across multiple correlated sensors.
• Identify the root cause of process stops.
• Send incident alerts.
The solution must minimize development time.
Which Azure service should you use?
Azure Metrics Advisor is an end-to-end service designed to perform anomaly detection in time-series data, which includes data ingestion, detecting anomalies, diagnosing anomalies to find root causes, and sending incident alerts. This service is specifically tailored to analyze multi-dimensional data from multiple sources, making it suitable for monitoring machinery sensors. By leveraging Azure Metrics Advisor, development time can be minimized due to its built-in capabilities and user-friendly interface that does not require deep machine learning knowledge, fulfilling all the requirements for anomaly detection, root cause identification, and incident alerting.
This came in the exam 28/06/2023
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.
"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
Quote "Use Metrics Advisor to: - Analyze multi-dimensional data from multiple data sources - Identify and correlate anomalies - Configure and fine-tune the anomaly detection model used on your data - Diagnose anomalies and help with root cause analysis" at https://learn.microsoft.com/en-us/azure/ai-services/metrics-advisor/overview
https://azure.microsoft.com/en-us/products/ai-services/ai-metrics-advisor What's the difference between AI Metrics Advisor and AI Anomaly Detector? AI Anomaly Detector is comprised of simple REST APIs with a code-first experience. It's the core engine of AI Metrics Advisor that detects anomalies in time-series data. It's best applied for ad-hoc data analysis, and it can be run in containers. AI Metrics Advisor has additional time-series monitoring features, with pipeline APIs and a built-in user interface for managing the service. It’s designed for live-streaming data and AI analytics, and it supports deploying in Azure.
Why is A?
The answer must be A since metrics advisor is specialized in multivariate analysis which is required by the question
Answer should indeed be A, I think. https://learn.microsoft.com/en-us/azure/applied-ai-services/metrics-advisor/overview as mentioned in other comments has both `Anomaly Detection` and `Incident reporting`
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.
Streaming data Metric Advisor where as batch data Anamoly detector.
A is the answer.
D is Correct for anomaly detection
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.
Metrics Advisor is that includes "root cause",
note the type of detection should be multivariate
correct answer is A https://learn.microsoft.com/en-us/azure/ai-services/metrics-advisor/overview
A. Azure Metrics Advisor Azure Metrics Advisor is a service that provides an end-to-end anomaly detection platform, which includes data ingestion, anomaly detection, root cause analysis, and alerting. It is designed to monitor and detect anomalies in time-series data, diagnose incidents, and provide insights.
Azure Metrics Advisor - collect time series data - detect anomalies - send incident alerts - analyze root cause