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Snowflake SnowPro® Specialty: Gen AI Certification Sample Questions:

1. A Gen AI Specialist is tasked with implementing a data pipeline to automatically enrich new customer feedback entries with sentiment scores using Snowflake Cortex functions. The new feedback arrives in a staging table, and the enrichment process must be automated and cost-effective. Given the following pipeline components, which combination of steps is most appropriate for setting up this continuous data augmentation process?

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

2. A data engineering manager needs to audit Cortex LLM function costs to identify specific SQL queries that are unexpectedly high in token consumption for the 'llama3.1-8b' model. They require granular analysis of prompt, completion, and guardrail token usage for these queries. Which of the following Snowflake methods or views would provide the necessary insights?

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

3. A data engineering team is building a pipeline to process legal documents using Snowflake Cortex functions. They aim to extract specific entities and summarize key clauses while being highly cost-conscious. To optimize token-based costs, which of the following practices should they implement when using Cortex LLM functions?

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

4. A data engineering team needs to establish an automated pipeline in Snowflake to continuously extract 'contract_id' and effective_date' from new PDF contract documents uploaded to an internal stage named They have a pre-trained Document AI model named 'contract_processor'. Which of the following sets of SQL commands correctly configures the necessary Snowflake objects for this automated processing pipeline, including handling file access and initial data loading?

A)

B)

C)

D)

E)

5. A data engineer is designing an automated pipeline in Snowflake to process streaming customer support tickets using LLM functions. To ensure the pipeline is robust against unexpected LLM errors (e.g., due to malformed input or transient service issues), they decide to use SNOWFLAKE.CORTEX.TRY_COMPLETE instead of SNOWF LAKE .CORTEX.COMPLETE
. Which of the following is the most significant advantage of using
TRY_COMPLETE
in this scenario?

A) It automatically adjusts the LLM's
B) It offers enhanced security features, such as automatic input sanitization, which are not available in the standard
C) It returns
D) It processes tokens at a significantly reduced rate compared to
E) It provides a built-in retry mechanism for LLM calls that encounter temporary failures, automatically re-submitting the prompt up to three times.

Solutions: