Google Cloud Professional Machine Learning Engineer — Question 97

You work on a team in a data center that is responsible for server maintenance. Your management team wants you to build a predictive maintenance solution that uses monitoring data to detect potential server failures. Incident data has not been labeled yet. What should you do first?

Answer options

• A. Train a time-series model to predict the machines’ performance values. Configure an alert if a machine’s actual performance values significantly differ from the predicted performance values.
• B. Develop a simple heuristic (e.g., based on z-score) to label the machines’ historical performance data. Use this heuristic to monitor server performance in real time.
• C. Develop a simple heuristic (e.g., based on z-score) to label the machines’ historical performance data. Train a model to predict anomalies based on this labeled dataset.
• D. Hire a team of qualified analysts to review and label the machines’ historical performance data. Train a model based on this manually labeled dataset.

Correct answer: C

Explanation

The correct answer is C because developing a heuristic to label historical performance data allows for the creation of a labeled dataset that can be used to train a model for anomaly detection. Option A skips the labeling step, which is crucial for accurate predictions. Option B does not involve training a model based on labeled data, while option D is resource-intensive and may delay the process without immediately addressing the need for predictive maintenance.