DP-203 Design and implement data storage Practice Question
You are migrating a large on-premises SQL Server database to Azure Synapse Analytics. The database includes tables with up to 500 million rows and frequent updates. You need to minimize data movement during the migration while ensuring optimal query performance in the dedicated SQL pool. Which table design strategy should you use?
⚠ Common exam trap
Many candidates assume hash-distributed tables are always the best choice for all tables, overlooking the fact that round-robin tables reduce data movement during migration and that hash distribution should be reserved for large fact tables to avoid skew and unnecessary shuffling.
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 round-robin tables for staging tables and hash-distributed tables for large fact tables on a key column.
It uses round-robin tables for staging to minimize data movement during the initial load, then hash-distributes large fact tables on a key column to optimize query performance by collocating rows with the same distribution key on the same compute node. This balances the need for fast ingestion with efficient parallel query execution in Azure Synapse Analytics dedicated SQL pools.
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 hash-distributed tables for all tables and clustered columnstore indexes.
Why it's wrong here
Hash-distributing every table, including small dimensions, forces data movement whenever those dimensions join large facts, and hash distribution on low-cardinality dimension keys creates skewed distributions. Hash distribution is intended for large fact tables; small dimensions belong in replicated tables to eliminate join movement.
- ✗
Use replicated tables for all fact tables and hash-distributed tables for dimension tables.
Why it's wrong here
Replicating fact tables copies every 500-million-row table to each compute node, and frequent updates must propagate to all copies, inflating write overhead and storage. Replication suits small dimension tables; the stem's large, frequently updated fact tables require hash distribution on a join column instead.
- ✗
Use round-robin tables for all tables to simplify the migration.
Why it's wrong here
Round-robin distribution spreads rows evenly without hashing on a join key, so every cross-table join triggers data movement and frequent updates cannot exploit partition elimination. It is tempting because round-robin loads fastest with no distribution-key decisions, which suits small staging or temporary tables rather than 500-million-row fact tables.
- ✓
Use round-robin tables for staging tables and hash-distributed tables for large fact tables on a key column.
Why this is correct
Round-robin distribution suits staging tables by balancing loads evenly without a join key, while hash distribution on a high-cardinality fact column co-locates related rows, reducing data movement during joins and aggregations in the dedicated SQL pool.
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This DP-203 practice question is part of Courseiva's free Microsoft certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the DP-203 exam.