Question 481 of 851

Secure, monitor, and optimize data storage and data processing →hardMultiple ChoiceObjective-mapped

DP-203 Practice Question: Secure, monitor, and optimize data storage and data processing

This DP-203 practice question tests your understanding of secure, monitor, and optimize data storage and data processing. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. 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 a data engineer for a global e-commerce company. The company uses Azure Synapse Analytics dedicated SQL pool for its data warehouse. The environment includes a large fact table 'Sales' distributed by hash on 'CustomerID', and dimension tables 'Customer' (hash-distributed on 'CustomerID') and 'Product' (replicated). Recently, queries that join Sales and Customer are performing poorly. You run a query to check data skew on the Sales table and find that one distribution has 40% more rows than the average. Additionally, the Customer table has high data movement during joins. You need to optimize the performance of these joins. What should you do?

A
Change the distribution of the Customer table to replicated.
Replicated tables avoid data movement for joins.
B
Increase the data warehouse performance level (DWU) to allocate more resources.
Why wrong: Scaling up does not fix data movement issues.
C
Change the distribution of the Sales table to round-robin.
Why wrong: Round-robin is not suitable for large fact tables.
D
Change the distribution key of the Sales table to 'ProductID' to align with the Product table.
Why wrong: Product is replicated, so no alignment needed; skew may remain.

Full breakdown with real-world context →

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

✓

Change the distribution of the Customer table to replicated.

The correct answer is to change the distribution of the Customer table to replicated. In Azure Synapse Analytics dedicated SQL pool, replicated tables are small enough to be cached on each compute node, eliminating the need to move data during joins. Since Customer is a dimension table, it is likely small enough to benefit from replication. This directly addresses the high data movement during joins. Option B (increasing DWU) would allocate more resources but does not fix the root cause of data movement and may only mask the issue. Option C (changing Sales to round-robin) is not recommended because fact tables in star schemas should be hash-distributed on a join key to minimize data movement. Option D (changing Sales distribution key to ProductID) would not improve the join with Customer unless the join is on ProductID, but the problem is with the Sales-Customer join; changing the distribution key to ProductID would affect the join with Product, not Customer, and could worsen the skew issue.

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.

✓
Change the distribution of the Customer table to replicated.
Why this is correct
Replicated tables avoid data movement for joins.
Related concept
CIDR notation defines the prefix length.
✗
Increase the data warehouse performance level (DWU) to allocate more resources.
Why it's wrong here
Scaling up does not fix data movement issues.
✗
Change the distribution of the Sales table to round-robin.
Why it's wrong here
Round-robin is not suitable for large fact tables.
✗
Change the distribution key of the Sales table to 'ProductID' to align with the Product table.
Why it's wrong here
Product is replicated, so no alignment needed; skew may remain.

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

An e-commerce site experiences heavy traffic on Black Friday and near-zero traffic during off-peak weeks. Rather than provisioning permanent large VMs, the team uses auto-scaling groups that add capacity automatically under load and reduce it overnight. Questions like this test whether you understand elasticity, availability zones, and cloud compute scaling patterns.

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?

Secure, monitor, and optimize data storage and data processing — This question tests Secure, monitor, and optimize data storage and data processing — CIDR notation defines the prefix length..

What is the correct answer to this question?

The correct answer is: Change the distribution of the Customer table to replicated. — The correct answer is to change the distribution of the Customer table to replicated. In Azure Synapse Analytics dedicated SQL pool, replicated tables are small enough to be cached on each compute node, eliminating the need to move data during joins. Since Customer is a dimension table, it is likely small enough to benefit from replication. This directly addresses the high data movement during joins. Option B (increasing DWU) would allocate more resources but does not fix the root cause of data movement and may only mask the issue. Option C (changing Sales to round-robin) is not recommended because fact tables in star schemas should be hash-distributed on a join key to minimize data movement. Option D (changing Sales distribution key to ProductID) would not improve the join with Customer unless the join is on ProductID, but the problem is with the Sales-Customer join; changing the distribution key to ProductID would affect the join with Product, not Customer, and could worsen the skew issue.

What should I do if I get this DP-203 question wrong?

What is the key concept behind this question?

CIDR notation defines the prefix length.

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