Microsoft Certified: Fabric Analytics Engineer AssociatePrepare and transform data (20-25%)Easy
A data engineer is designing a data ingestion solution for a new e-commerce platform. The platform generates transactional data in real-time as JSON messages through an Azure Event Hub. These messages need to be captured, transformed, and loaded into a Lakehouse table with minimal latency for near real-time analytics. Which Microsoft Fabric component is specifically designed to ingest and process streaming data from Event Hubs?
- AData Pipelines
- BEventstream
- CDataflows Gen2
- DSpark notebook with batch processing
Show answer & explanationAnswer & explanation
Correct answer: B. Eventstream
Eventstream is a real-time analytics component in Microsoft Fabric specifically designed for ingesting, transforming, and routing streaming data from sources like Azure Event Hubs with low latency.
Why the other options are wrong
- A. Data Pipelines are for orchestrating batch data movement and transformations, not real-time stream processing.
- C. Dataflows Gen2 is primarily for batch processing and scheduled refreshes, not real-time streaming ingestion.
- D. While Spark can do real-time processing (Spark Streaming/Structured Streaming), a Spark notebook typically implies batch processing unless specifically configured for streaming, and Eventstream offers a more integrated, often low-code, solution for this specific scenario.
Eventstream
A real-time analytics capability in Microsoft Fabric for ingesting, transforming, and routing streaming data from various sources.
- Low-latency processing.
- Supports Event Hubs, Kafka, custom apps.
- Integrates with other Fabric items like Lakehouse.
Memory trick: Eventstream: The river for your real-time data.