DEA-C02 Data Governance Practice Question
A healthcare company implements a Row Access Policy (RAP) on a PATIENTS table to restrict doctor access to only their assigned patients. The RAP references a mapping table. What is the most critical performance consideration when designing this policy for a table with billions of rows?
⚠ Common exam trap
Candidates often focus on the complexity of the policy logic, ignoring that the join with a large mapping table is the primary bottleneck for performance on massive datasets.
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
✓
Ensuring the mapping table is small and uses columns that allow for effective pruning.
When Row Access Policies involve joins to mapping tables, Snowflake's optimizer must execute these checks efficiently to avoid full table scans. Using a memoizable function or ensuring the mapping table is small and clustered correctly helps the pruning process. Governance at scale requires balancing strict security logic with the underlying query performance to ensure user experience is maintained.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Applying the policy to the mapping table itself to prevent circular references.
Why it's wrong here
While preventing circular references is important for policy logic, it is not the primary performance concern for large-scale data sets. Applying a policy to the mapping table can actually increase complexity and overhead without addressing the core issue of how the main table's rows are filtered during execution.
- ✓
Ensuring the mapping table is small and uses columns that allow for effective pruning.
Why this is correct
The performance of a Row Access Policy depends heavily on how well Snowflake can prune data. If the mapping table is large or poorly structured, the policy evaluation can become a bottleneck. Keeping mapping tables lean and indexed via clustering ensures that the join logic does not force unnecessary data scanning.
- ✗
Using a CASE statement instead of a WHERE clause within the policy definition.
Why it's wrong here
The internal syntax of the policy (CASE vs WHERE) does not fundamentally change how the optimizer handles the underlying join to the mapping table. Performance is dictated by the data volume and the ability of the engine to prune micro-partitions, rather than the specific conditional syntax used within the SQL.
- ✗
Granting the OWNERSHIP privilege of the mapping table to the PUBLIC role.
Why it's wrong here
Granting ownership to the PUBLIC role is a significant security risk and does not impact the execution speed of the Row Access Policy. Governance best practices dictate that the mapping table should be tightly controlled, and performance should be addressed through physical data modeling and efficient SQL join patterns.
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.