Quick Answer
The correct answer is Delta Lake on Azure Databricks and Azure Event Hubs. Delta Lake provides the unified batch and streaming storage layer with built-in schema evolution, allowing you to write both batch and streaming data into the same Delta table while automatically handling schema changes like column additions or type promotions through its ACID transactions and time-travel capabilities. Azure Event Hubs complements this by ingesting real-time streaming data and capturing it directly into Azure Data Lake Storage Gen2, creating a single source of truth for both processing modes. On the DP-203 exam, this tests your understanding of how to design a medallion architecture (bronze-silver-gold) where schema evolution is critical for streaming data that may change structure over time. A common trap is choosing Azure Synapse Analytics or Azure Stream Analytics alone, which lack native schema evolution support. Remember the mnemonic “DELTA for Data, EVENTS for Entry” to pair the storage engine with the ingestion service.
This DP-203 practice question tests your understanding of design and develop data processing. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
You are designing a data processing solution in Azure that must handle both batch and streaming data. The solution should use a common storage layer for both and support schema evolution. Which TWO technologies should you recommend?
Azure Event Hubs
Common ingestion for batch and streaming.
Azure SQL Database
Why wrong: Not designed for streaming.
Apache Kafka on HDInsight
Why wrong: Less integrated with Azure ecosystem.
Delta Lake (on Azure Databricks)
Supports batch and streaming, schema evolution.
Azure Data Lake Storage Gen2
Why wrong: Storage layer, not processing.
Answer choices
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 correct because it is a fully managed, real-time data ingestion service that can capture streaming data and store it in Azure Data Lake Storage Gen2 or Blob Storage, enabling a unified storage layer for both batch and streaming pipelines. It supports schema evolution through Avro or JSON serialization, allowing downstream consumers to adapt to schema changes without breaking existing processes.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
Azure Event Hubs
Why this is correct
Common ingestion for batch and streaming.
Related concept
Read the scenario before looking for a memorised answer.
Azure SQL Database
Why it's wrong here
Not designed for streaming.
Apache Kafka on HDInsight
Why it's wrong here
Less integrated with Azure ecosystem.
Delta Lake (on Azure Databricks)
Why this is correct
Supports batch and streaming, schema evolution.
Related concept
Read the scenario before looking for a memorised answer.
Azure Data Lake Storage Gen2
Why it's wrong here
Storage layer, not processing.
Common exam traps
The trap here is that candidates often confuse Azure Data Lake Storage Gen2 as a processing technology rather than a storage layer, or they overlook that Event Hubs is the streaming ingestion service that pairs with Delta Lake for unified batch/streaming and schema evolution.
Detailed technical explanation
Delta Lake uses a transaction log (stored as JSON files in a _delta_log directory) to track schema changes, allowing ACID-compliant schema evolution via ALTER TABLE ADD COLUMN or overwriteSchema options. Event Hubs supports Capture, which automatically writes streaming data to Avro files in ADLS Gen2, enabling batch processing on the same data without custom code. In a real-world scenario, a retail company might ingest clickstream data via Event Hubs, capture it to ADLS Gen2, and use Delta Lake on Databricks to run both real-time dashboards and nightly batch aggregations, with schema evolution handling new event fields added by developers.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
A media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
What to study next
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Design and develop data processing — study guide chapter
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FAQ
Design and develop data processing — This question tests Design and develop data processing — Read the scenario before looking for a memorised answer..
The correct answer is: Azure Event Hubs — Azure Event Hubs is correct because it is a fully managed, real-time data ingestion service that can capture streaming data and store it in Azure Data Lake Storage Gen2 or Blob Storage, enabling a unified storage layer for both batch and streaming pipelines. It supports schema evolution through Avro or JSON serialization, allowing downstream consumers to adapt to schema changes without breaking existing processes.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 11, 2026
This DP-203 practice question is part of Courseiva's free Microsoft certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the DP-203 exam.
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