Microsoft Certified: Azure Fundamentals (AZ-900) Practice Exam

The best-suited Azure service for analyzing large volumes of streaming IoT data is HDInsight. This service provides a fully-managed cloud service that makes it easy to process and analyze big data. HDInsight supports various big data frameworks such as Apache Hadoop, Spark, and Kafka, which are particularly useful for handling streaming data and performing real-time analytics.

With HDInsight, you can leverage its capabilities to efficiently analyze IoT data streams, allowing for insights and actions to be derived from incoming data in real-time. This makes it an ideal choice for scenarios where large volumes of continuously generated data need to be processed quickly, such as in IoT applications.

Other recommendations, while useful in their contexts, don't specifically cater to the unique requirements of streaming IoT data analysis. For instance, Machine Learning service primarily focuses on building predictive models rather than processing streaming data itself. Application Insights is geared towards monitoring application performance and usage rather than processing large-scale data streams. Data Lake Analytics can analyze large datasets but is more suitable for batch processing rather than real-time streaming analytics.