DP-203 Develop data processing Practice Question
Which TWO components are required to set up a streaming data pipeline using Azure Synapse Analytics? (Select two.)
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
To set up a streaming data pipeline in Azure Synapse Analytics, you need a streaming ingestion source and a processing engine. Azure Event Hubs (Option B) is the correct ingestion service for real-time streaming data. Azure Synapse Pipelines (or Spark) (Option E) provides the processing engine to transform and analyze the streaming data. Azure Data Factory (Option A) is primarily for batch data integration, not streaming. Azure Analysis Services (Option C) is for OLAP modeling, not streaming. Azure Blob Storage (Option D) is a storage destination, not a required component for streaming ingestion or processing.
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
Azure Data Factory provides batch-orchestrated copy activities and scheduled pipelines, not the continuous low-latency event ingestion a streaming pipeline requires; Synapse's own Stream Analytics or Event Hubs integration supplies that. It is tempting because it is Azure's primary data-integration tool, and it would be correct for scheduled batch movement into the warehouse.
- ✓
Azure Event Hubs
Why this is correct
Azure Event Hubs provides the ingestion endpoint for high-throughput streaming data, satisfying the pipeline's requirement for a scalable event broker. Synapse Spark or Stream Analytics can then read from it for near-real-time processing. Without an ingestion source, no streaming pipeline exists, making Event Hubs a required component.
- ✗
Azure Analysis Services
Why it's wrong here
Azure Analysis Services hosts tabular semantic models for BI querying; it neither ingests nor processes streaming events, so it cannot form part of the pipeline. It is tempting because it is a genuine Azure analytics service, and it would be correct when serving pre-aggregated tabular models to Power BI over a warehouse.
- ✗
Azure Blob Storage
Why it's wrong here
Azure Blob Storage is a batch object store; it offers no native streaming ingestion endpoint, so events cannot flow through it in real time. It is tempting because Synapse can query blob data via external tables, and it would be correct when landing batch files for later analytical processing.
- ✓
Azure Synapse Pipelines (or Spark)
Why this is correct
Azure Synapse Pipelines or Spark provides the compute that ingests and transforms the stream, satisfying the requirement for a processing engine within the workspace. Streaming ingestion cannot occur without this orchestration or transformation layer, which pairs with a target store such as a dedicated SQL pool to complete the pipeline.
Quick reference
Azure Blob Storage Tier Comparison
| Tier | Storage Cost | Retrieval Cost | Latency | Use Case |
|---|---|---|---|---|
| Hot | Highest | Lowest | Immediate | Active data, frequent reads |
| Cool | Lower | Higher | Immediate | Data accessed < once / month |
| Cold | Lower still | Higher | Immediate | Data accessed < once / quarter |
| Archive | Lowest | Highest + rehydration delay | Hours | Long-term compliance retention |
Go deeper
Related to this question
Learn chapter
Implement Azure Synapse Analytics
Key term
Azure Data Factory
Azure Data Factory is a cloud-based data integration service that lets you create, schedule, and orchestrate data pipelines to move and transform data from various sources to destinations.
Key term
Azure Synapse Analytics
Azure Synapse Analytics is a cloud-based data integration, warehousing, and analytics service that brings together big data and data warehouse capabilities under one platform.
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