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

Which TWO actions can you take to optimize the performance of an Azure Synapse Analytics dedicated SQL pool? (Choose two.)

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

Replicate small dimension tables.

Replicating small dimension tables across all distributions reduces data movement during joins and improves query performance. Option E is correct because hash distribution on a column used in joins and aggregations ensures that rows with the same key are colocated on the same distribution, minimizing data shuffling. Option A is incorrect: scaling up increases resources but is not a targeted performance optimization and may not address underlying distribution or indexing issues. Option C is incorrect: heap indexes are generally not optimal for fact tables because they lack compression and indexing benefits; clustered columnstore indexes are recommended. Option D is incorrect: round-robin distribution distributes data evenly but does not reduce data movement for joins and aggregations, often leading to poor query performance.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Scale up the SQL pool to a higher DWU.

    Why it's wrong here

    Scaling up increases resources but is not a specific optimization technique.

  • Replicate small dimension tables.

    Why this is correct

    Replication reduces data movement for joins with fact tables.

  • Use heap indexes for fact tables.

    Why it's wrong here

    Heaps are not recommended for data warehouse workloads.

  • Use round-robin distribution for all large fact tables.

    Why it's wrong here

    Round-robin distributes evenly but does not optimize joins.

  • Use hash distribution on a column used in joins and aggregations.

    Why this is correct

    Reduces data movement during joins and aggregations.

Visual reference

Client Server SYN (seq=100) SYN-ACK (seq=200, ack=101) ACK (ack=201) Connection established — data transfer begins

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Written by Johnson Ajibi, MSc IT Security

Senior Network & Security Engineer · founder of Courseiva

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