DEA-C02 Performance Optimization Practice Question
Which of the following is the most cost-effective way to handle massive concurrent read-only queries?
⚠ Common exam trap
Candidates often select 'Maximizing' scaling policy, thinking it is the best for performance, but it ignores the cost-effectiveness requirement specified in the question for handling massive read-only concurrency.
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 a multi-cluster warehouse with economy scaling.
Multi-cluster warehouses are designed specifically to handle high concurrency. By setting the scaling policy to 'Economy', Snowflake adds clusters only when the queue grows, prioritizing cost over immediate startup. This allows the system to scale horizontally to meet demand without requiring manual intervention, effectively balancing user experience with credit consumption. It is the standard solution for environments where dashboard traffic spikes and performance must be maintained without over-provisioning compute resources.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Increase the warehouse size.
Why it's wrong here
Increasing the warehouse size scales compute vertically, which helps with individual query performance but does nothing to solve concurrency issues. If many users are running queries simultaneously, a single larger warehouse will still experience contention, and you will be paying for more power than is actually required.
- ✓
Use a multi-cluster warehouse with economy scaling.
Why this is correct
Multi-cluster warehouses scale horizontally to handle high concurrency. The 'Economy' policy specifically optimizes for cost by being more conservative about adding new clusters, which is ideal for read-only workloads where some queuing is acceptable to save credits compared to the 'Standard' policy.
- ✗
Enable query pruning.
Why it's wrong here
Query pruning is an automatic feature that improves the performance of individual queries by reducing the amount of data read. It does not address concurrency or high traffic loads. Even with optimal pruning, a single warehouse will eventually face performance degradation if the number of concurrent users is high.
- ✗
Create materialized views for every user.
Why it's wrong here
Creating materialized views for every user is not scalable and would significantly increase storage and maintenance costs. Materialized views should be used for common, shared data access patterns, not as a mechanism for handling individual user concurrency, which is better managed by scaling the compute infrastructure.
About these practice questions
Courseiva writes every DEA-C02 question from scratch — 229 in total, each with an explanation and a wrong-answer breakdown. None are copied from real exams or dumps. Learn why practice questions differ from exam dumps →
JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Snowflake exam blueprint
This DEA-C02 practice question is part of Courseiva's free Snowflake 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 DEA-C02 exam.