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You are using Azure Stream Analytics to process real-time data from IoT devices. The devices send temperature readings, and you need to detect and alert when the temperature exceeds a certain threshold. Which of the following approaches would be most suitable for implementing this scenario?
A
Use a batch processing approach and store the data in a temporary storage before processing.
B
Implement a custom deserialization logic to handle the temperature readings.
C
Use the built-in 'SELECT' statement with a threshold comparison to filter the temperature readings and output the results to an alerting service.
D
Leverage Azure Machine Learning to predict temperature thresholds and send alerts based on the predictions.