- A
Use a broadcast hash join to distribute the smaller table to all nodes.
Broadcast join avoids shuffling large data, reducing skew impact.
- B
Increase the Data Integration Units (DIU) in the data flow.
Why wrong: Adding DIU improves parallelism but does not fix the underlying skew; skewed partitions remain slow.
- C
Use the 'Optimize' tab in the data flow to enable skewed data optimization.
This feature automatically handles skewed data by splitting skewed partitions.
- D
Apply a salting technique by adding a random salt to the join key.
Salting distributes skewed keys across more partitions, reducing skew.
- E
Repartition the data on a different column using a random distribution.
Why wrong: Repartitioning may help but is not a direct skew optimization; it could even worsen performance.
Quick Answer
The answer is applying a salting technique by adding a random salt to the join key, alongside using skewed data optimization and a broadcast hash join. These three techniques directly address data skew by redistributing uneven workloads: salting breaks hot keys into sub-partitions, skewed data optimization automatically detects and handles imbalanced partitions, and broadcast hash join sends the smaller dataset to all nodes, avoiding costly shuffles. On the DP-203 exam, this scenario tests your ability to optimize Mapping Data Flows under real-world data distribution challenges, often appearing as a multiple-select question where increasing DIUs (Option A) is a common trap—it adds compute but does not fix the root cause of skew. Remember the mnemonic "S-B-S" for Salt, Broadcast, Skew—if you see these three, you are set to balance the load.
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 optimizing an Azure Synapse Pipeline that processes large volumes of data using a Mapping Data Flow. The pipeline is taking too long due to data skew. Which THREE techniques can help mitigate data skew?
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 broadcast hash join to distribute the smaller table to all nodes.
Option B (use skewed data optimization), Option D (broadcast hash join), and Option E (salting the key) are techniques to handle skew in data flows. Option A (increasing DIU) adds resources but doesn't address skew. Option C (repartition) can help but is not a direct skew mitigation; broadcast join is more effective.
Key principle: Count usable hosts — not total addresses — and remember that the network and broadcast addresses are not available to hosts in standard IPv4 subnets.
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 a broadcast hash join to distribute the smaller table to all nodes.
Why this is correct
Broadcast join avoids shuffling large data, reducing skew impact.
Related concept
CIDR notation defines the prefix length.
- ✗
Increase the Data Integration Units (DIU) in the data flow.
Why it's wrong here
Adding DIU improves parallelism but does not fix the underlying skew; skewed partitions remain slow.
- ✓
Use the 'Optimize' tab in the data flow to enable skewed data optimization.
Why this is correct
This feature automatically handles skewed data by splitting skewed partitions.
Related concept
CIDR notation defines the prefix length.
- ✓
Apply a salting technique by adding a random salt to the join key.
Why this is correct
Salting distributes skewed keys across more partitions, reducing skew.
Related concept
CIDR notation defines the prefix length.
- ✗
Repartition the data on a different column using a random distribution.
Why it's wrong here
Repartitioning may help but is not a direct skew optimization; it could even worsen performance.
Common exam traps
Common exam trap: usable hosts are not the same as total addresses
Subnetting questions often tempt you into counting all addresses. In normal IPv4 subnets, the network and broadcast addresses are not usable host addresses.
Detailed technical explanation
How to think about this question
Subnetting questions test whether you can identify the network, broadcast address, usable range, mask and correct subnet. Slow down enough to calculate the block size correctly.
KKey Concepts to Remember
- CIDR notation defines the prefix length.
- Block size helps identify subnet boundaries.
- Network and broadcast addresses are not usable hosts in normal IPv4 subnets.
- The required host count determines the smallest suitable subnet.
TExam Day Tips
- Write the block size before choosing the subnet.
- Check whether the question asks for hosts, subnets or a specific address range.
- Do not confuse /24, /25, /26 and /27 host counts.
Key takeaway
Count usable hosts — not total addresses — and remember that the network and broadcast addresses are not available to hosts in standard IPv4 subnets.
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. Count usable hosts — not total addresses — and remember that the network and broadcast addresses are not available to hosts in standard IPv4 subnets. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
What to study next
Got this wrong? Here's your next step.
Review block sizes, usable host formulas (2^n − 2), and how to find network and broadcast addresses for /24 through /30. Then practise related DP-203 subnetting questions on CIDR, address ranges, and subnet selection.
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FAQ
Questions learners often ask
What does this DP-203 question test?
Develop data processing — This question tests Develop data processing — CIDR notation defines the prefix length..
What is the correct answer to this question?
The correct answer is: Use a broadcast hash join to distribute the smaller table to all nodes. — Option B (use skewed data optimization), Option D (broadcast hash join), and Option E (salting the key) are techniques to handle skew in data flows. Option A (increasing DIU) adds resources but doesn't address skew. Option C (repartition) can help but is not a direct skew mitigation; broadcast join is more effective.
What should I do if I get this DP-203 question wrong?
Review block sizes, usable host formulas (2^n − 2), and how to find network and broadcast addresses for /24 through /30. Then practise related DP-203 subnetting questions on CIDR, address ranges, and subnet selection.
What is the key concept behind this question?
CIDR notation defines the prefix length.
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Last reviewed: Jun 21, 2026
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