The correct approach is to create an external table in serverless SQL pool that points to the Delta Lake folder and query it directly. This works because serverless SQL pool natively supports the Delta Lake format, allowing it to read the latest version of the data as Stream Analytics continuously writes new commits to Azure Data Lake Storage Gen2. By pointing the external table’s LOCATION directly at the Delta folder, you achieve minimal latency without any data movement or transformation, since the pool reads the most recent snapshot of the Delta transaction log in real time. On the DP-203 exam, this scenario tests your understanding of serverless SQL pool’s native Delta Lake integration versus common traps like using a view over Parquet files or requiring a data copy step. A key memory tip is “Delta direct, no redirect”—serverless SQL pool queries Delta Lake files in place, so avoid any intermediate staging or conversion steps that would add latency.
DP-203 Develop data processing Practice Question
This DP-203 practice question tests your understanding of 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 streaming solution in Azure Synapse Analytics using the serverless SQL pool to query streaming data in real-time. The data is ingested via Azure Event Hubs and processed using Azure Stream Analytics. The output of Stream Analytics is written to Azure Data Lake Storage Gen2 in Delta Lake format. You need to ensure that the serverless SQL pool can query the latest data with minimal latency. Which approach should you use?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Create an external table in serverless SQL pool that points to the Delta Lake folder and query it directly.
Option D is correct because serverless SQL pool can directly query Delta Lake format files stored in Azure Data Lake Storage Gen2 by creating an external table with LOCATION pointing to the Delta folder. This allows real-time querying of the latest streaming data without any data movement or transformation, achieving minimal latency since Stream Analytics writes continuously to Delta Lake.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
✗
Ingest data directly from Event Hubs into serverless SQL pool using CETAS (CREATE EXTERNAL TABLE AS SELECT).
Why it's wrong here
Serverless SQL pool does not have real-time ingestion capabilities.
✗
Use a materialized view in serverless SQL pool that refreshes every minute.
Why it's wrong here
Serverless SQL pool does not support materialized views.
✗
Load the streaming data into a dedicated SQL pool using a scheduled pipeline and then query it from serverless SQL pool.
Why it's wrong here
This adds latency and is not real-time.
✓
Create an external table in serverless SQL pool that points to the Delta Lake folder and query it directly.
Why this is correct
Serverless SQL pool supports Delta Lake format and can query it as soon as data is written.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates may confuse serverless SQL pool with dedicated SQL pool and assume features like materialized views or scheduled pipelines are available, or they may think CETAS can directly ingest from Event Hubs, which is not supported.
Detailed technical explanation
How to think about this question
Delta Lake format stores data as Parquet files with a transaction log (_delta_log) that tracks changes; serverless SQL pool uses the Delta Lake connector to read the latest snapshot by parsing the transaction log, enabling near-real-time queries. In practice, Stream Analytics can output to Delta Lake with a small batch interval (e.g., every 10 seconds), and the external table in serverless SQL pool reflects that data almost immediately without needing to refresh or move data.
KKey Concepts to Remember
Read the scenario before looking for a memorised answer.
Find the constraint that changes the correct option.
Eliminate answers that are true in general but not in this case.
TExam Day Tips
→Watch for words such as best, first, most likely and least administrative effort.
→Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
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.
Related glossary terms
Concepts from this question explained
These glossary pages explain the core terms tested in this DP-203 question in full detail.
Develop data processing — This question tests Develop data processing — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Create an external table in serverless SQL pool that points to the Delta Lake folder and query it directly. — Option D is correct because serverless SQL pool can directly query Delta Lake format files stored in Azure Data Lake Storage Gen2 by creating an external table with LOCATION pointing to the Delta folder. This allows real-time querying of the latest streaming data without any data movement or transformation, achieving minimal latency since Stream Analytics writes continuously to Delta Lake.
What should I do if I get this DP-203 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Question Discussion
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