The answer is outdated or missing statistics on the tables. This is the most likely cause because the Azure Synapse Analytics dedicated SQL pool query optimizer relies on accurate statistics to estimate row counts and data distribution; without them, it cannot distinguish between a selective index seek and a full table scan, often defaulting to the latter on large fact tables, which directly explains the slow query performance due to outdated statistics. On the DP-203 exam, this tests your understanding of how the optimizer’s cost-based decisions fail without fresh metadata—a common trap is blaming indexing or partitioning first, when the root cause is stale statistics. Remember the mnemonic: “Stats stale, scans prevail.”
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.
Your organization is using Azure Synapse Analytics dedicated SQL pool. You notice that queries are running slower than expected. Upon reviewing the execution plans, you see that some queries are performing table scans instead of seeks on large fact tables. What is the most likely cause?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue: "most likely"
Why it matters: Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
The statistics on the tables are outdated or missing.
Outdated or missing statistics prevent the Azure Synapse Analytics dedicated SQL pool query optimizer from accurately estimating row counts and data distribution. Without reliable statistics, the optimizer may incorrectly choose a table scan over a more efficient index seek or partition elimination, leading to slower query performance on large fact tables.
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.
✓
The statistics on the tables are outdated or missing.
Why this is correct
Outdated or missing statistics can cause the optimizer to choose suboptimal access methods like table scans.
Clue confirmation
The clue word "most likely" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
✗
The tables are distributed using round-robin distribution.
Why it's wrong here
Round-robin distribution distributes data evenly but does not directly cause table scans.
✗
Result-set caching is disabled.
Why it's wrong here
Result-set caching improves repeated query performance but does not affect the access method.
✗
The resource class for the user is set to smallrc.
Why it's wrong here
Resource class affects concurrency and memory allocation, not the access method.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse performance issues caused by distribution type or resource class with the optimizer's reliance on statistics, overlooking that even with optimal distribution and sufficient resources, stale statistics force scans instead of seeks.
Detailed technical explanation
How to think about this question
In Azure Synapse dedicated SQL pool, the query optimizer relies on statistics histograms to estimate selectivity and choose appropriate access methods. When statistics are outdated (e.g., after significant data modifications without an UPDATE STATISTICS or AUTO_UPDATE_STATISTICS event), the optimizer may assume a large portion of rows match a predicate, leading it to favor a full table scan over an index seek. Real-world scenarios include nightly ETL loads that insert millions of rows without triggering automatic statistic updates, causing degraded performance until statistics are refreshed manually or via a maintenance job.
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 cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
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: The statistics on the tables are outdated or missing. — Outdated or missing statistics prevent the Azure Synapse Analytics dedicated SQL pool query optimizer from accurately estimating row counts and data distribution. Without reliable statistics, the optimizer may incorrectly choose a table scan over a more efficient index seek or partition elimination, leading to slower query performance on large fact tables.
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.
Are there clue words in this question I should notice?
Yes — watch for: "most likely". Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
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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