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Microsoft Exam AI-102 Topic 3 Question 51 Discussion

Actual exam question for Microsoft's AI-102 exam
Question #: 51
Topic #: 3
[All AI-102 Questions]

You are developing a monitoring system that will analyze engine sensor data, such as rotation speed, angle, temperature, and pressure. The system must generate an alert in response to atypical values.

What should you include in the solution?

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Suggested Answer: A

by Chauncey at Oct 07, 2023, 11:19 PM

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Kris
18 days ago
If this was a car engine, I'd say Option B is the way to go. Gotta keep an eye on those metrics, like the engine's vital signs.
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Cecily
2 days ago
User 1: I agree, Option B with metric alerts sounds like the best choice for monitoring engine sensor data.
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Nathalie
21 days ago
Option C all the way! Multivariate Anomaly Detection is like the Marvel team of anomaly detection - it can handle multiple superheroes (er, sensor data points) at once.
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Noemi
23 days ago
Hold up, why are we even considering Application Insights (Option A)? That's more for web apps, not industrial sensor monitoring.
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Chanel
2 days ago
A) Application Insights in Azure Monitor
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Darrin
1 months ago
Hmm, I'm not sure if Univariate Anomaly Detection (Option D) is the right fit here. Analyzing each sensor data point in isolation might miss the bigger picture.
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Veronique
4 days ago
C) Multivariate Anomaly Detection
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Destiny
21 days ago
B) metric alerts in Azure Monitor
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Emogene
1 months ago
A) Application Insights in Azure Monitor
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Sherita
2 months ago
I'd go with Option B. Metric alerts in Azure Monitor seem tailored for this use case, as they can trigger alerts based on predefined thresholds for the sensor data.
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Latrice
1 months ago
I agree, Option B seems like the most suitable solution for monitoring engine sensor data.
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Yvonne
1 months ago
Option B) metric alerts in Azure Monitor is a good choice for this. It can help trigger alerts based on predefined thresholds for sensor data.
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Sophia
2 months ago
Option C looks like the best choice for this monitoring system. Multivariate Anomaly Detection can analyze multiple sensor data points to identify atypical patterns.
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Rashad
2 months ago
I think we should also consider using metric alerts in Azure Monitor to quickly respond to any anomalies.
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Polly
2 months ago
I agree with Serina, Multivariate Anomaly Detection can help us detect complex patterns in the sensor data.
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Serina
2 months ago
I think we should include Multivariate Anomaly Detection in the solution.
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