Snowflake Start Focus
Log In Create Account

DSA-C03 workspace

Detailed Explanations

A detailed answer review with side-by-side rationale, distractor analysis, related questions, and weak-topic practice.

Certification
Build Quiz

DSA-C03 catalog review

4.0 Model Deployment

Correct: A
Your answer Not answered Answer this in practice or the daily question to sync here.
Correct answer A Managing model versions and metadata
Result Awaiting answer Synced from this browser when available.
Confidence Unset Use the practice page confidence controls to calibrate this item.

What is the primary role of the Snowflake Model Registry in a deployment workflow?

A Managing model versions and metadata
B Creating external cloud buckets
C Replacing feature engineering
D Tracking table retention policies
1. Answer captured 2. Key checked 3. Rationale review 4. Retry weak topic

Detailed explanation

Catalog rationale

Correct answer: A

A deployed Snowflake ML workflow normally starts by logging a trained model to the Model Registry. The registry provides versioning, metadata, access control, and entry points for running or serving the model.

Key concept 4.0 Model Deployment

SnowPro Advanced- Data Scientist (DSA-C03)

Exam tip Map the requirement to the managed Snowflake capability.

Eliminate services that solve infrastructure, data movement, or routing when the stem asks for AI model access or governance.

Snowflake service references

03 SnowPro Advanced- Data Scientist (DSA-C03) 04 4.0 Model Deployment SnowPro Advanced- Data Scientist (DSA-C03) 4.0 Model Deployment

Why the wrong answers are wrong

B

Incorrect. Cloud buckets are configured through stages and integrations, not the model registry.

C

Incorrect. Feature engineering still has to be designed and validated before deployment.

D

Incorrect. Retention policies govern data history, not model lifecycle management.