Answer-first summary for fast verification
Answer: Use Azure Stream Analytics to process the data in real-time as it is generated by the IoT devices, leveraging Azure Event Hubs for data ingestion and Azure Functions for additional processing.
Option B is the correct answer. Using Azure Stream Analytics to process the data in real-time as it is generated by the IoT devices ensures efficient and timely data processing. Leveraging Azure Event Hubs for data ingestion allows you to handle high-throughput and scalable data streams. Azure Functions can be used for additional processing tasks, providing a serverless compute option for event-driven scenarios.
Author: LeetQuiz Editorial Team
Ultimate access to all questions.
Your company is using Azure AI services to analyze and process data from IoT devices. The data generated by these devices is time-sensitive and requires real-time processing. What strategies should you implement to ensure efficient and timely data processing?
A
Store the data in Azure Blob Storage and process it in batches at regular intervals.
B
Use Azure Stream Analytics to process the data in real-time as it is generated by the IoT devices, leveraging Azure Event Hubs for data ingestion and Azure Functions for additional processing.
C
Disable real-time processing and rely on manual data processing by the AI service.
D
Use Azure Data Lake Storage to store the data and process it using Azure Databricks, ignoring the need for real-time processing.
No comments yet.