DP-203 Practice Question: Secure, monitor, and optimize data storage and data processing
You are a data engineer at a financial services company. Your Azure Synapse Analytics dedicated SQL pool contains a fact table named 'Transactions' with 10 billion rows. The table is hash-distributed on 'AccountID' and partitioned by month. You notice that queries filtering on 'TransactionDate' (a date column) are performing slowly despite partition elimination. You also observe that the 'Transactions' table is frequently joined with a 'DimAccount' dimension table on 'AccountID'. You need to optimize query performance for the most common workload: monthly reports that aggregate transaction amounts by account for the last 12 months. Additionally, you need to ensure that the solution minimizes maintenance overhead. 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
✓
Create a clustered columnstore index on the table
Creating a clustered columnstore index on the 'Transactions' fact table provides column-level compression and significantly improves scan performance for aggregation queries, which is ideal for monthly reports aggregating transaction amounts. Option B is wrong because redistributing on TransactionDate using hash distribution would not improve join performance with DimAccount (which joins on AccountID) and may cause data skew if many rows share the same date. Option C is wrong because changing distribution to round-robin would eliminate collocation benefits for joins on AccountID, hurting query performance. Option D is wrong because table replication is designed for small dimension tables, not large fact tables like 'Transactions' with billions of rows.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Create a clustered columnstore index on the table
Why this is correct
Improves compression and scan performance for aggregations
- ✗
Redistribute the table on TransactionDate using hash distribution
Why it's wrong here
Causes data skew, not optimal for partitioning
- ✗
Change distribution to round-robin to evenly distribute data
Why it's wrong here
Loses join collocation with DimAccount
- ✗
Use table replication for the Transactions table
Why it's wrong here
Replication is for small dimension tables, not large fact tables
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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