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Snowflake SnowPro® Specialty: Gen AI Certification Sample Questions:

1. An enterprise is deploying a new RAG application using Snowflake Cortex Search on a large dataset of customer support tickets. The operations team is concerned about managing compute costs and ensuring efficient index refreshes for the Cortex Search Service, which needs to be updated hourly. Which of the following considerations and configurations are relevant for optimizing cost and performance of the Cortex Search Service in this scenario?

A) The primary cost driver for Cortex Search is the number of search queries executed against the service, with the volume of indexed data (GBImonth) having a minimal impact on overall billing.
B) For embedding text, selecting a model like

C) CHANGE_TRACKING
D) For optimal performance and cost efficiency, Snowflake recommends using a dedicated warehouse of size no larger than MEDIUM for each Cortex Search Service.
E) The

2. A data engineering team is building a pipeline in Snowflake that uses a SQL task to call various Snowflake Cortex LLM functions (e.g., AI_COMPLETE, AI EMBED) on large datasets of customer interaction logs. The team observes fluctuating costs and occasional query failures, which sometimes halt the pipeline. To address these issues and ensure an efficient, robust, and monitorable pipeline, which of the following actions or considerations are essential? (Select all that apply.)

A) Option A
B) Option D
C) Option B
D) Option E
E) Option C

3. A team is building a critical Document AI pipeline for continuous processing of new financial reports. They've identified that occasionally, the 'GET_PRESIGNED_URL' generated for specific documents expires before the '!PREDICT function can successfully process them, resulting in HTTP 403 errors. To mitigate this, they plan to modify their SQL query logic.
Which approach effectively addresses the presigned URL expiration issue without altering the stage definition or the model build itself, and adheres to recommended practices for handling batch processing as described in Snowflake's troubleshooting documentation?

A)

B)

C)

D)

4.
After resolving this, they try to process a batch of 1500 documents in a single query using the method, which also fails. Which two issues are most likely contributing to these failures?

A) The has not been granted the 'CREATE STREAM' privilege on the
B) The virtual warehouse being used for Document AI is not a Snowpark-optimized warehouse.
C) The name is not unique within the .
D) The 'SNOWFLAKE.DOCUMENT INTELLIGENCE CREATOR database role or the 'CREATE SNOWFLAKE.ML.DOCUMENT INTELLIGENCE' privilege on the schema has not been granted to the .
E) The batch of documents exceeds Document AI's limit of 1000 documents per query.

5.

A) The 'ACCOUNTADMIN' must execute the SQL command:

B) The parameter provides granular control at the database or schema level, allowing administrators to define different sets of approved models for different data contexts.
C) Enabling Cortex Guard for 'AI_COMPLETE through the 'guardrails' option automatically bypasses the 'CORTEX_MODELS_ALLOWLIST to ensure all LLMs can be used for content safety filtering.
D) Users with 'ds_team_role' will still be able to successfully call

E) If a user attempts to call an LLM not explicitly listed in the via the Cortex LLM Playground, Snowflake will automatically fall back to the 'snowflake-arctic' model for that request.

Solutions: