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Snowflake SnowPro® Specialty: Gen AI Certification Sample Questions:

1. A data engineering team needs to configure their Snowflake environment to process documents using AI_PARSE_DOCUMENT and generate text embeddings using EMBED_TEXT_1024 with the voyage-multilingual-2 model. Their Snowflake account is in a region where these specific capabilities or models are only available via cross-region inference. The team needs to ensure these functions work correctly without constant region-specific model selection. Which of the following is the correct configuration action and an important consideration?

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

2. 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 (GB/month) having a minimal impact on overall billing.
B) For optimal performance and cost efficiency, Snowflake recommends using a dedicated warehouse of size no larger than MEDIUM for each Cortex Search Service.
C) The

D) CHANGE_TRACKING
E) For embedding text, selecting a model like

3. A financial analyst is concerned about the rising costs of their Document AI pipeline, which uses to extract data from daily financial reports. They observe that their assigned 'LARGE virtual warehouse is running continuously, even during periods of low document ingestion, contributing significantly to their bill. They want to investigate how to reduce costs effectively for their existing Document AI setup.

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

4. 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) For debugging, Cortex Agents allow direct modification of the LLM's internal state to refine accuracy, latency, and cost during execution.
B) 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.
C) 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).
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 are restricted to using only Snowflake's native Cortex LLM functions; custom logic via UDFs or stored procedures is not supported for tool implementation.

5. A new Gen AI team member attempts to use Document AI to process a batch of 1 ,500 scanned image files (JPG) that are 70 MB each, stored in an internal stage that was created without specifying an encryption type. Their '!PREDICT' queries consistently fail with various errors. Which of the following are valid reasons for the '!PREDICT' queries to fail in this scenario?

A) The team member's role lacks the database role, which is essential for using Document AI functions.
B) The internal stage was not created with 'ENCRYPTION = (TYPE = 'SNOWFLAKE SSE'V, which is a requirement for Document AI.
C) The individual JPG files exceed the maximum supported file size for Document AI.
D) Processing 1 ,500 documents in one query exceeds the maximum limit for Document AI.
E) JPG is an unsupported file format for Document AI.

Solutions: