DP-203 Develop data processing Practice Question
You are designing a data processing solution in Azure Synapse Analytics. The solution must support both batch and streaming data ingestion. Which Azure service should you use to ingest streaming data into Synapse Analytics?
⚠ Common exam trap
DP-203 often tests the confusion between batch ingestion (Data Factory) and streaming ingestion (Event Hubs / IoT Hub / Kafka), so candidates who pick Data Factory for 'ingestion' miss the streaming requirement.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Azure Event Hubs
Azure Event Hubs is Microsoft's managed, real-time event-ingestion service designed for high-throughput streaming scenarios, and it integrates natively with Azure Synapse Analytics (via the Synapse Event Hubs connector or Spark Structured Streaming) to land streaming data into dedicated SQL pools, Spark pools, or the lake. It is the canonical answer for streaming ingestion into Synapse.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Azure Data Factory
Why it's wrong here
Data Factory orchestrates batch pipelines and scheduled copies; its streaming capability is limited to ingestion into specific sinks and does not provide the continuous event processing this scenario needs. It is tempting because it already handles batch ingestion, but the streaming path in Synapse is served by Azure Stream Analytics or Event Hubs.
- ✗
Azure Blob Storage
Why it's wrong here
Blob Storage stores objects; it has no native streaming ingestion pipeline into Synapse SQL pools or Spark tables, so events cannot be consumed continuously. It is tempting as the landing zone for batch files, and would suit archival or staged batch loads, but streaming requires an engine that reads and writes events in motion.
- ✓
Azure Event Hubs
Why this is correct
Azure Event Hubs ingests high-throughput streaming data and integrates natively with Synapse Analytics through its dedicated connector, satisfying the stem's streaming ingestion requirement. Unlike batch-only pipelines, Event Hubs captures continuous telemetry in real time, landing events directly into Synapse SQL pools or Spark tables for immediate processing.
- ✗
Azure Analysis Services
Why it's wrong here
Analysis Services hosts semantic tabular models for BI querying; it consumes processed data and cannot ingest streaming events into Synapse. It is tempting because it sits in the analytics stack and serves reporting, but it is a query and modelling layer, not an ingestion service, so it fails the streaming requirement entirely.
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Last reviewed September 2026 · checked against the official Microsoft exam blueprint
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