The answer is to use CREATE TABLE AS SELECT (CTAS) with the hash-distributed column. This pattern is the most efficient for loading into a hash-distributed fact table because CTAS writes data directly into the target table using the same distribution scheme, eliminating the need for costly data movement or redistribution during the load. By leveraging Synapse Analytics’ MPP architecture, CTAS parallelizes the bulk insert across all distributions, minimizing resource contention and allowing concurrent queries to run with minimal impact. On the DP-203 exam, this scenario tests your understanding of how to optimize large-scale data ingestion in a dedicated SQL pool, often contrasting CTAS with INSERT...SELECT or PolyBase external tables—common traps that cause blocking or excessive shuffling. Remember the key distinction: CTAS is a DDL operation that creates and populates the table in one atomic step, while INSERT...SELECT is a DML operation that locks the table. Memory tip: “CTAS loads and creates, no locks or data fates.”
DP-203 Efficient load into Synapse dedicated pool Practice Question
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 have a Synapse Analytics dedicated SQL pool. You need to load 100 GB of CSV data from Azure Data Lake Storage Gen2 into a fact table. The table has a hash-distributed column. Which pattern is most efficient for loading with minimal impact on concurrent queries?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Use CREATE TABLE AS SELECT (CTAS) with the hash-distributed column
Option B is correct because CTAS with a hash-distributed column loads data directly into the target table with the same distribution scheme, avoiding data movement and minimizing resource contention. This pattern is optimized for bulk loading large datasets into a hash-distributed fact table, as it leverages the Synapse SQL pool's MPP architecture to parallelize the operation without blocking concurrent queries.
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 PolyBase INSERT...SELECT with rowstore table
Why it's wrong here
INSERT...SELECT logs each row and may cause concurrency issues; not as efficient as CTAS for large loads.
✗
Use COPY INTO command with a round-robin distribution
Why it's wrong here
COPY INTO is efficient but round-robin distribution may cause data movement later; CTAS with hash distribution avoids extra steps.
✗
Use Azure Data Factory Copy activity with staging enabled
Why it's wrong here
Copy activity with staging uses PolyBase under the hood but adds overhead; CTAS is more direct.
Option-by-option analysis
Why each answer is right or wrong
Understanding why wrong answers are wrong — and when they would be correct — is what separates a 750 score from a 900. The DP-203 exam frequently reuses these exact scenarios with slightly different constraints.
✓Use CREATE TABLE AS SELECT (CTAS) with the hash-distributed columnCorrect answer▾✗Use PolyBase INSERT...SELECT with rowstore tableWrong answer — click to see why▾
Why this is wrong here
INSERT...SELECT logs each row and may cause concurrency issues; not as efficient as CTAS for large loads.
✗Use COPY INTO command with a round-robin distributionWrong answer — click to see why▾
Why this is wrong here
COPY INTO is efficient but round-robin distribution may cause data movement later; CTAS with hash distribution avoids extra steps.
✗Use Azure Data Factory Copy activity with staging enabledWrong answer — click to see why▾
Why this is wrong here
Copy activity with staging uses PolyBase under the hood but adds overhead; CTAS is more direct.
Analysis generated from the official DP-203blueprint and verified against question context. The “when correct” sections are what AI assistants cite when candidates ask “what’s the difference between these options?”
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often assume PolyBase or COPY INTO are always the fastest for bulk loading, but they overlook that CTAS with the correct distribution key avoids the costly data redistribution step required by other methods.
Detailed technical explanation
How to think about this question
CTAS in Synapse SQL pool executes as a distributed query that reads the source data in parallel across all compute nodes, directly writing each partition to the correct distribution based on the hash key. This avoids the need for a separate INSERT...SELECT or redistribution step, as the hash distribution is applied during the table creation, making it the most efficient pattern for large-scale loads into hash-distributed fact tables. In real-world scenarios, CTAS can also be used with partition switching to minimize downtime, but the core benefit is the elimination of data movement overhead.
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.
Design and develop data processing — This question tests Design and 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 CREATE TABLE AS SELECT (CTAS) with the hash-distributed column — Option B is correct because CTAS with a hash-distributed column loads data directly into the target table with the same distribution scheme, avoiding data movement and minimizing resource contention. This pattern is optimized for bulk loading large datasets into a hash-distributed fact table, as it leverages the Synapse SQL pool's MPP architecture to parallelize the operation without blocking concurrent queries.
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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