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 data lake. Source files arrive daily in Parquet format in Azure Data Lake Storage Gen2. The data must be cleaned, aggregated, and loaded into an Azure Synapse SQL pool. The solution should minimize compute costs and management overhead. Which technology should you use for the transformation?
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 the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Azure Synapse Pipelines with mapping data flows.
Option C is correct because Synapse Pipelines (built on ADF) can orchestrate mapping data flows that run on serverless Spark clusters, minimizing management overhead. Option A (HDInsight) requires cluster management. Option B (Databricks) incurs higher costs for simple batch. Option D (SSIS) is legacy and not cloud-native.
Key principle: NAT direction and interface roles matter as much as the IP address mapping. Inside/outside designation controls which traffic is translated.
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 HDInsight with Spark jobs scheduled in Azure Data Factory.
Why it's wrong here
HDInsight requires manual cluster management and is overkill for simple batch transformations.
✓
Azure Synapse Pipelines with mapping data flows.
Why this is correct
Mapping data flows in Synapse Pipelines provide serverless, code-free transformation with minimal management.
Clue confirmation
The clue word "minimum / minimize" in the question point toward this answer.
Related concept
Static NAT maps one inside address to one outside address.
✗
Azure Data Factory with a custom SSIS package.
Why it's wrong here
SSIS is legacy and requires an Azure-SSIS IR, adding complexity and cost.
✗
Azure Databricks with an Auto Loader pipeline.
Why it's wrong here
Databricks is more expensive and better suited for complex analytics or streaming.
Common exam traps
Common exam trap: NAT rules depend on direction and matching traffic
NAT is not only about the public address. The inside/outside interface roles and the ACL or rule that matches traffic are just as important.
Detailed technical explanation
How to think about this question
NAT questions usually test address translation, overload/PAT behaviour, static mappings and whether the right traffic is being translated. Read the interface direction and address terms carefully.
KKey Concepts to Remember
Static NAT maps one inside address to one outside address.
PAT allows many inside hosts to share one public address using ports.
Inside local and inside global describe the private and translated addresses.
NAT ACLs identify traffic for translation, not always security filtering.
TExam Day Tips
→Identify inside and outside interfaces first.
→Check whether the scenario needs static NAT, dynamic NAT or PAT.
→Do not confuse NAT matching ACLs with normal packet-filtering intent.
Key takeaway
NAT direction and interface roles matter as much as the IP address mapping. Inside/outside designation controls which traffic is translated.
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.
Related glossary terms
Concepts from this question explained
These glossary pages explain the core terms tested in this DP-203 question in full detail.
Review the four NAT address types (inside local, inside global, outside local, outside global), PAT port overload, and static vs dynamic NAT use cases. Then practise related DP-203 NAT questions on configuration and troubleshooting.
Develop data processing — This question tests Develop data processing — Static NAT maps one inside address to one outside address..
What is the correct answer to this question?
The correct answer is: Azure Synapse Pipelines with mapping data flows. — Option C is correct because Synapse Pipelines (built on ADF) can orchestrate mapping data flows that run on serverless Spark clusters, minimizing management overhead. Option A (HDInsight) requires cluster management. Option B (Databricks) incurs higher costs for simple batch. Option D (SSIS) is legacy and not cloud-native.
What should I do if I get this DP-203 question wrong?
Review the four NAT address types (inside local, inside global, outside local, outside global), PAT port overload, and static vs dynamic NAT use cases. Then practise related DP-203 NAT questions on configuration and troubleshooting.
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?
Static NAT maps one inside address to one outside address.
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Question Discussion
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