DP-203 Practice Question: Secure, monitor, and optimize data storage and data processing
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?
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.
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.
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.
- ✗
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.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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