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A logistics company needs to track millions of packages in real-time. Each package generates telemetry data (location, temperature, status) every few seconds. This data needs to be ingested, processed, and analyzed to detect anomalies and provide real-time dashboards. The data will also be used for historical reporting over several months. Which Azure data integration solution is best suited to collect and process this continuous stream of data for real-time analytics?
- AAzure Logic Apps
- BAzure Stream Analytics
- CAzure Synapse Analytics
- DAzure Data Factory
Show answer & explanationAnswer & explanation
Correct answer: B. Azure Stream Analytics
Azure Stream Analytics is a real-time analytics service designed for processing large streams of data from various sources (like IoT devices). It can perform complex event processing (CEP) to detect patterns, anomalies, and aggregate data for real-time dashboards and subsequent storage.
Why the other options are wrong
- A. Azure Logic Apps are for serverless workflow automation and integration, not for high-volume, real-time data stream processing.
- C. Azure Synapse Analytics is a unified analytics platform for data warehousing and big data, optimized for batch processing and complex analytical queries, not real-time stream processing.
- D. Azure Data Factory is an ETL/ELT service for batch processing and orchestrating data movement, not for real-time stream processing.
Azure Stream Analytics
A real-time analytics service that enables you to develop and deploy low-cost solutions for complex event processing over fast-moving streams of data.
- Processes data from Event Hubs, IoT Hub, and Blob Storage.
- Supports SQL-like query language for stream processing.
- Ideal for real-time dashboards, anomaly detection, and alerts.
Memory trick: Streams analyze data, fast and bright.