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Snowflake SnowPro® Specialty: Gen AI Certification Sample Questions:

1. An enterprise is deploying a Cortex Analyst application and needs to manage its cost, ensure data security, and understand its operational behavior within Snowflake. Which of the following statements are true regarding the deployment, cost, and security of Cortex Analyst and its semantic models?

A) Semantic models for Cortex Analyst, stored as YAML files in a Snowflake stage, should have their stage access controlled by RBAC to implicitly control access to the underlying tables referenced in the semantic model.
B) Cortex Analyst applications are fully managed, and by default, all data, including metadata and prompts, remain within Snowflake's governance boundary when using Snowflake-hosted LLMs from Mistral and Meta.
C) The CORTEX_ANALYST_USER database role is sufficient for making requests to Cortex Analyst, and the cost incurred is solely based on the number of tokens processed by the underlying LLMs, not per message.
D) Administrators can monitor Cortex Analyst requests, including the user, question asked, generated SQL, and errors, by querying the SNOWFLAK LOCAL. CORTEX ANALYST_REQUESTS function.
E) Enabling the account parameter is the recommended approach for using Azure OpenAI models with Cortex Analyst to ensure the highest performance and adherence to RBAC restrictions.

2. A data application developer is building a Streamlit chat application within Snowflake. This application uses a RAG pattern to answer user questions about a knowledge base, leveraging a Cortex Search Service for retrieval and an LLM for generating responses. The developer wants to ensure responses are relevant, concise, and structured. Which of the following practices are crucial when integrating Cortex Search with Snowflake Cortex LLM functions like AI_COMPLETE for this RAG chatbot?

A) Using the

B) The retrieved context from Cortex Search should be directly concatenated with the user's prompt as input to the
C) For performance and cost optimization, it is always recommended to query Cortex Search and the LLM function within a single
D) The

E) To maintain conversational context in a multi-turn chat, the developer should pass all previous user prompts and model responses in the

3. A company wants to ingest and process scanned invoices and digitally-born contracts in Snowflake. They need to extract all text, preserving layout for contracts and just the text content for scanned invoices. Which AI_PARSE_DOCUMENT modes would be most appropriate for this scenario, and what is the primary purpose of the function itself?

A) Primary purpose is to extract data and layout. For contracts, use LAYOUT mode; for invoices, use OCR mode.
B) Primary purpose is to generate new text. For contracts, use OCR mode; for invoices, use LAYOUT mode.
C) Primary purpose is to translate text. Both document types should use LAYOUT mode.
D) Primary purpose is to summarize text. For contracts, use OCR mode; for invoices, use LAYOUT mode.
E) Primary purpose is to classify text. For contracts, use LAYOUT mode; for invoices, use OCR mode.

4. A new data analyst is trying to incorporate sentiment analysis using SNOWFLAKE. CORTEX. SENTIMENT within a Snowflake data pipeline that uses dynamic tables. They execute the following SQL to create a dynamic table for daily sentiment aggregation:

However, this operation fails. Which of the following is the most direct reason for the failure of this specific setup?

A) The CORTEX_USER database role was not granted to the analyst's role, preventing the execution of Cortex functions.
B) SNOWFLAKE. CORTEX. SENTIMENT and other Snowflake Cortex functions are currently incompatible with dynamic tables.
C) The warehouse my_analytics_wh is likely not a Snowpark-optimized warehouse, which is a requirement for Cortex functions within dynamic tables.
D) The TARGET_LAG for dynamic tables must be explicitly set to '1 day' or longer when integrating with Cortex functions.
E) The review_content column, if containing non-English text, would cause the SENTIMENT function to fail outright rather than produce inaccurate results.

5. A data engineering team is building an automated pipeline within Snowflake to process newly ingested documents. This pipeline needs to classify each document's sentiment (positive, neutral, negative) and summarise its content using Cortex LLM functions, then store the results in a table. The pipeline is orchestrated using Streams and Tasks. Which considerations are paramount for implementing and monitoring this AI-infused data pipeline?

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

Solutions: