Microsoft Certified: Azure AI Engineer AssociatePlan and manage an Azure AI solutionEasy
A company is developing an Azure AI solution that will process large volumes of real-time sensor data from IoT devices. The solution needs to ingest data from thousands of devices concurrently and process it for anomaly detection using Azure Machine Learning. Which Azure service should be used to efficiently ingest this high-throughput data stream into the Azure AI solution?
- AAzure Data Lake Storage Gen2
- BAzure Event Hubs
- CAzure Blob Storage
- DAzure SQL Database
Show answer & explanationAnswer & explanation
Correct answer: B. Azure Event Hubs
Azure Event Hubs is specifically designed for highly scalable, real-time data ingestion from millions of devices, making it ideal for IoT scenarios.
Why the other options are wrong
- A. Azure Data Lake Storage Gen2 is suitable for large-scale data storage and analytics but not optimized for high-throughput real-time ingestion.
- C. Azure Blob Storage is an object storage solution best for static or infrequently accessed data, not high-throughput real-time ingestion.
- D. Azure SQL Database is a relational database and not designed for ingesting large volumes of real-time streaming data efficiently.
Azure Event Hubs
A highly scalable data streaming platform and event ingestion service capable of handling millions of events per second.
- Designed for big data streaming scenarios.
- Supports high throughput and low latency.
- Integrates with other Azure services for processing and analytics.
Memory trick: Event Hubs handles the 'rush hour' of data streams.