- A
Use Azure Databricks with Auto Loader to read from Data Lake Storage, perform transformations using Spark SQL, and write to the dedicated SQL pool via JDBC.
Why wrong: Azure Databricks is an external service with additional management overhead and cost.
- B
Use Azure Data Factory with Mapping Data Flows to visually design transformations and write to the dedicated SQL pool.
Why wrong: Mapping Data Flows run on Spark clusters, incurring costs; also not SQL-based.
- C
Create a Spark job definition in Azure Synapse that reads Parquet files, performs transformations using PySpark, and writes to the dedicated SQL pool using the Spark Synapse connector.
Why wrong: Spark pools incur costs; PySpark is not SQL.
- D
Use a serverless SQL pool in Azure Synapse to query the Parquet files using T-SQL, then use CETAS to write the results to the dedicated SQL pool.
Serverless SQL pool is cost-effective for ad-hoc querying; CETAS allows moving data to dedicated pool.
Quick Answer
The answer is to use a serverless SQL pool in Azure Synapse with CETAS. This approach is correct because serverless SQL pool can directly query Parquet files in Azure Data Lake Storage Gen2 using standard T-SQL, and the CREATE EXTERNAL TABLE AS SELECT (CETAS) statement writes the transformed results into a dedicated SQL pool without provisioning any Spark clusters. For the DP-203 exam, this scenario tests your understanding of cost-optimized batch processing: the trap is assuming complex transformations require Spark, but serverless SQL pool handles joins, aggregations, and window functions natively at a fraction of the cost. Remember that CETAS bridges the serverless and dedicated worlds—think of it as "query cheap, land fast." A useful memory tip: CETAS is like a SQL-based conveyor belt that moves transformed data from cheap serverless compute straight into your dedicated pool, avoiding the Spark price tag entirely.
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 batch processing solution for a financial services company that processes transactions from multiple sources. The data is stored in Azure Data Lake Storage Gen2 in Parquet format. You need to perform complex transformations including joins, aggregations, and window functions, and then load the results into an Azure Synapse Analytics dedicated SQL pool. The transformations must be written in SQL and executed on a serverless Spark cluster to minimize costs. You want to manage the code in a Git repository and automate the deployment using Azure DevOps. Which approach should you recommend?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue:
"minimum / minimize"Why it matters: Asks for the least resource use — fewest addresses, smallest subnet, lowest overhead. Eliminate over-provisioned options even if they would technically work.
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
Use a serverless SQL pool in Azure Synapse to query the Parquet files using T-SQL, then use CETAS to write the results to the dedicated SQL pool.
Option B is correct because Synapse Serverless SQL pool can query Parquet files directly using T-SQL, and you can use CREATE EXTERNAL TABLE AS SELECT (CETAS) to write results to the dedicated SQL pool. This avoids Spark costs and uses serverless compute. Option A uses Spark, which costs more. Option C uses Azure Databricks, which is external and adds complexity. Option D uses Azure Data Factory with Data Flows that run on Spark, also incurring costs.
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.
- ✗
Use Azure Databricks with Auto Loader to read from Data Lake Storage, perform transformations using Spark SQL, and write to the dedicated SQL pool via JDBC.
Why it's wrong here
Azure Databricks is an external service with additional management overhead and cost.
- ✗
Use Azure Data Factory with Mapping Data Flows to visually design transformations and write to the dedicated SQL pool.
Why it's wrong here
Mapping Data Flows run on Spark clusters, incurring costs; also not SQL-based.
- ✗
Create a Spark job definition in Azure Synapse that reads Parquet files, performs transformations using PySpark, and writes to the dedicated SQL pool using the Spark Synapse connector.
Why it's wrong here
Spark pools incur costs; PySpark is not SQL.
- ✓
Use a serverless SQL pool in Azure Synapse to query the Parquet files using T-SQL, then use CETAS to write the results to the dedicated SQL pool.
Why this is correct
Serverless SQL pool is cost-effective for ad-hoc querying; CETAS allows moving data to dedicated pool.
Clue confirmation
The clue word "minimum / minimize" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Detailed technical explanation
How to think about this question
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
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.
- Use explanations to understand the rule behind the answer.
TExam Day Tips
- Underline the problem statement mentally.
- 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 startup's cloud architect reviews their monthly bill and notices costs are higher than expected for a long-running batch job. Switching from on-demand instances to Reserved Instances — or using Spot/Preemptible VMs — can reduce compute costs by up to 72 %. Questions like this test whether you understand the tradeoffs between commitment, flexibility, and cost across cloud pricing models.
What to study next
Got this wrong? Here's your next step.
Identify which DP-203 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
- →
Develop data processing — study guide chapter
Learn the concepts, then practise the questions
- →
Develop data processing practice questions
Targeted practice on this topic area only
- →
All DP-203 questions
846 questions across all exam domains
- →
Microsoft Azure Data Engineer Associate DP-203 study guide
Full concept coverage aligned to exam objectives
- →
DP-203 practice test guide
How to use practice tests most effectively before exam day
Related practice questions
Related DP-203 practice-question pages
Use these pages to review the topic behind this question. This is how one missed question becomes focused revision.
Secure, monitor, and optimize data storage and data processing practice questions
Practise DP-203 questions linked to Secure, monitor, and optimize data storage and data processing.
Design and develop data processing practice questions
Practise DP-203 questions linked to Design and develop data processing.
Design and implement data security practice questions
Practise DP-203 questions linked to Design and implement data security.
Monitor and optimize data storage and processing practice questions
Practise DP-203 questions linked to Monitor and optimize data storage and processing.
Design and implement data storage practice questions
Practise DP-203 questions linked to Design and implement data storage.
Develop data processing practice questions
Practise DP-203 questions linked to Develop data processing.
DP-203 fundamentals practice questions
Practise DP-203 questions linked to DP-203 fundamentals.
DP-203 scenario practice questions
Practise DP-203 questions linked to DP-203 scenario.
DP-203 troubleshooting practice questions
Practise DP-203 questions linked to DP-203 troubleshooting.
Practice this exam
Start a free DP-203 practice session
Short sessions build daily habit. Longer sessions build exam-day stamina. Try a timed session to simulate real conditions.
FAQ
Questions learners often ask
What does this DP-203 question test?
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: Use a serverless SQL pool in Azure Synapse to query the Parquet files using T-SQL, then use CETAS to write the results to the dedicated SQL pool. — Option B is correct because Synapse Serverless SQL pool can query Parquet files directly using T-SQL, and you can use CREATE EXTERNAL TABLE AS SELECT (CETAS) to write results to the dedicated SQL pool. This avoids Spark costs and uses serverless compute. Option A uses Spark, which costs more. Option C uses Azure Databricks, which is external and adds complexity. Option D uses Azure Data Factory with Data Flows that run on Spark, also incurring costs.
What should I do if I get this DP-203 question wrong?
Identify which DP-203 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
Are there clue words in this question I should notice?
Yes — watch for: "minimum / minimize". Asks for the least resource use — fewest addresses, smallest subnet, lowest overhead. Eliminate over-provisioned options even if they would technically work.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
Last reviewed: Jun 21, 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.
Question Discussion
Share a tip, memory trick, or ask about the reasoning behind this question. Do not post real exam questions, leaked content, braindumps, or copyrighted exam material. Comments are moderated and may be removed without notice.
Sign in to join the discussion.