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Snowflake SnowPro® Specialty: Gen AI Certification Sample Questions:

1.

A)

B)

C)

D) Cross-region inference is automatically managed by Snowflake for allowed models, implying that a new, larger virtual warehouse is required to handle the cross- region data transfer overhead.
E)

2. A data engineer is working with Snowflake Cortex Analyst to improve its ability to answer natural language questions by precisely identifying product names for filtering. They have decided to integrate a Cortex Search Service with their semantic model to enhance literal search for the 'product_name' dimension. Which of the following configurations within the semantic model's YAML file are valid and effective for this purpose?

A) Including in the semantic model's 'metrics' section, referencing 'product_name'.
B) Setting true' for the 'product_name' dimension and providing an exhaustive list of to restrict the model to only those values.
C) Only specifying 'sample_valueS for the 'product_name' dimension without a entry.
D) Adding a 'cortex_search_service' entry to the 'product_name' dimension with only the 'service' field:

E) Adding a entry to the 'product_name' dimension, including 'literal_column' and ensuring the search service is configured to index the physical column:

3. A data engineer is designing an automated data pipeline in Snowflake to process incoming customer feedback documents. The pipeline needs to perform the following steps: 1. Extract the overall sentiment from the feedback text. 2. Generate a concise summary of each feedback document. 3. Extract key entities (e.g., product, issue, customer name) into a structured JSON format using a powerful LLM, ensuring adherence to a predefined schema and graceful error handling. Which of the following Snowflake Cortex features and best practices should the data engineer leverage to build this robust AI-infused pipeline?

A) Option D
B) Option E
C) Option C
D) Option A
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. An enterprise is designing an advanced generative AI application in Snowflake, leveraging Cortex Agents to orchestrate data analysis from both structured and unstructured sources. According to Snowflake's Gen AI principles and the capabilities of Cortex Agents, which of the following statements accurately describe the workflow components and the types of tools an agent can utilize?

A) Cortex Agents are restricted to using only Snowflake's native Cortex LLM functions; custom logic via UDFs or stored procedures is not supported for tool implementation.
B) For debugging, Cortex Agents allow direct modification of the LLM's internal state to refine accuracy, latency, and cost during execution.
C) The agent's workflow includes 'Planning' to orchestrate a solution, 'Explore options' for disambiguation, and 'Reflection' to determine next steps after tool use. Supported tools include Cortex Analyst and Cortex Search.
D) Cortex Agents primarily focus on pre-defined, single-turn SQL queries for structured data, with limited support for unstructured data processing.
E) Cortex Agents can orchestrate across both structured and unstructured data sources, and custom tools can be implemented using Snowflake stored procedures and user-defined functions (UDFs).

Solutions: