Which two components should you include in the workflow? Each correct answer presents part of the solution.

A time-based schedule is for batch processing at fixed intervals, not typically for continuous real-time workflows.

A streaming dataflow is essential for ingesting, transforming, and processing real-time data streams continuously, making it suitable for scenarios requiring immediate data handling.

A blob storage action is for interacting with Azure Blob Storage, which might be a component of a data pipeline but not a core 'component of the workflow' in the sense of real-time processing and action.

A data pipeline is an orchestration tool, capable of including streaming dataflows, but it's not the streaming component itself.

A notebook using Apache Spark Structured Streaming could process streaming data, but 'streaming dataflow' (B) is a more specific Fabric item designed for streaming ingestion and transformation, complementing a reflex item for real-time actions.