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Answer: Use Azure Event Hubs to ingest the data and then use Stream Analytics to process the data, handle schema drift, and create windowed aggregates for traffic analysis.
Option D is the correct approach as it covers all the necessary components of a stream processing solution for traffic analysis in a smart city project. Azure Event Hubs is used to ingest the data, Stream Analytics is used to process the data, handle schema drift, and create windowed aggregates. This approach ensures that the solution can handle real-time data from various sources and provide insights into traffic patterns and congestion.
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You are tasked with developing a stream processing solution for a smart city project that needs to analyze real-time traffic data from various sources, such as cameras and sensors. The data is being ingested into Azure Event Hubs. How would you approach creating a solution using Stream Analytics and Azure Event Hubs?
A
Use Stream Analytics to create a query that reads data from Azure Event Hubs and writes the output to a storage account.
B
Use Azure Event Hubs to ingest the data and then use Stream Analytics to process the data and create windowed aggregates for traffic analysis.
C
Use Azure Event Hubs to ingest the data and then use Stream Analytics to process the data and handle schema drift for traffic analysis.
D
Use Azure Event Hubs to ingest the data and then use Stream Analytics to process the data, handle schema drift, and create windowed aggregates for traffic analysis.