A company manufactures automobile parts. The company installs IoT sensors on manufacturing machinery. You must design a solution that analyzes data from the sensors. You need to recommend a solution…

Azure Analysis Services is typically used for complex data modeling and querying for business intelligence, not as the primary component for real-time ingestion or initial processing of raw IoT data.

Configuring an Azure Event Hub to capture data to Azure Data Lake Storage ensures that all raw sensor data, even after real-time processing, is persistently stored for future ETL operations and historical analysis, meeting the data availability requirement.

Developing an Azure Stream Analytics application that queries the data and outputs to Power BI directly addresses the real-time analysis requirement and enables visualization through charts and graphs, with support for continuous integration of queries.

Developing an application that sends the IoT data to an Azure Event Hub is critical for high-volume data ingestion, as Event Hubs are highly scalable and performant services designed specifically for ingesting millions of events per second from various sources.

This choice is a duplicate of choice C and offers no additional distinct action for the solution.

Developing an application to send IoT data directly to an Azure Data Lake Storage container is less efficient for high-volume, real-time ingestion compared to using an Event Hub, which is purpose-built for such scenarios.