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Snowflake SnowPro® Specialty: Gen AI Certification Sample Questions:

1. An operations team is investigating an issue with a generative AI application powered by Snowflake Cortex Analyst, where users reported unexpected behavior in generated SQL. To diagnose the problem, they examine the detailed event logs captured by Snowflake AI Observability. Which categories of information can they expect to find in these event tables to assist their investigation?

A) Any error messages or warnings that occurred during the processing of the request.
B) The exact SQL queries that Cortex Analyst generated in response to user questions.
C) Real-time CPU and memory usage statistics for the Snowflake virtual warehouse executing the LLM inference.
D) The complete request and response bodies associated with the application's execution steps.
E) The full text of the natural language questions submitted by the users.

2. A financial institution uses Snowflake to process an average of 5 million PDF documents (average 10 pages each) monthly for regulatory compliance using AI_PARSE_DOCUMENT in LAYOUT mode. They are monitoring costs and considering performance optimizations. Given this scenario, which of the following statements about cost and performance for AI_PARSE_DOCUMENT are true?

A) The primary billing metric for in LAYOUT mode is the number of tokens processed, which includes both input and output tokens.
B) If a document is a HTML file, the billing is based on processing each chunk of 3,000 characters as a page.
C) To reduce costs, the team should aim to process documents in batches, ensuring each query processes a maximum of 1 ,000 documents to avoid errors.
D) For optimal results with multilingual documents, the LAYOUT mode supports a broader range of languages than OCR mode.
E) Selecting a 'LARGE' or 'X-LARGE' standard warehouse will significantly improve the processing speed and reduce the per-page cost for AI_PARSE_DOCUMENT.

3. A Snowflake administrator needs to implement a granular access control strategy for LLMs. The general policy is to restrict access to a select few models via an account-level allowlist. However, a specific data science team (using role 'DATA SCIENCE TEAM ROLE) requires access to the 'claude-3-5-sonnet' model, which should not be available to other users or globally via the allowlist. Given this scenario, which set of commands would correctly establish this access control while adhering to the specified requirements?

A)

B)

C)

D)

E)

4. A data engineering team is preparing a large corpus of unstructured text documents for a Retrieval Augmented Generation (RAG) application in Snowflake, leveraging Cortex Search and LLM functions. They plan to use SNOWFLAKE.CORTEX.SPLIT_TEXT_RECURSIVE_CHARACTER as part of their data ingestion pipeline. What is the primary benefit of employing this helper function in the context of their RAG workflow?

A) It divides lengthy documents into smaller, manageable text chunks, which improves the precision of information retrieval and the relevance of downstream LLM responses.
B) It performs sentiment analysis on each chunk, allowing the RAG system to filter out negative or irrelevant content before retrieval.
C) It generates vector embeddings for each document chunk, eliminating the need for separate embedding models.
D) It automatically translates documents into a target language, ensuring multilingual compatibility for the LLM.
E) It compresses the text data to reduce storage costs in Snowflake stages before processing by embedding models.

A) The ACCOUNTADMIN role to ensure unrestricted access to all Snowflake Cortex features.
B)

C)

D) The USAGE privilege on the specific database and schema where the Streamlit application and its underlying data tables are located.
E) The CREATE COMPUTE POOL privilege to provision resources for the Streamlit application.