Snowflake GES-C01 Practice Questions

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Snowflake SnowPro® Specialty: Gen AI Certification Exam Sample Questions (Q97-Q102):

NEW QUESTION # 97
A data engineering team is implementing a solution using Snowflake Cortex's AI_COMPLETE function to process customer support tickets. They are concerned about sensitive information and ensuring the model's responses are safe, while adhering to Snowflake's data governance principles. Which of the following statements correctly describe the functionality of Cortex Guard and Snowflake's data privacy commitments in this context?

Answer: A,D

Explanation:
Option B is correct because Cortex Guard evaluates the LLM's responses, not just the prompts, to filter unsafe content. Additionally, only the input tokens for Cortex Guard are counted for billing, and this cost is in addition to the function's cost. Option E is correct because Snowflake's trust and safety principles explicitly state that your Usage and Customer Data (including inputs and outputs of Snowflake AI Features) are NOT available to other customers and are NOT used to train, re-train, or fine-tune Models made available to others. Option A is incorrect as customer data is not anonymised and used to improve general model performance for others. Option C is incorrect as the sources do not mention fine-tuning a customer-owned guardrail model. Option D is incorrect as the sources do not mention a 'CORTEX GUARD ADMIN' role or logging of filtered content to a customer-accessible audit table.


NEW QUESTION # 98
A security auditor needs to access and analyze logs generated by Snowflake AI Observability for compliance auditing and to track the activity of generative AI applications. They need to understand how to reliably query this data and its temporal characteristics within Snowflake. Which of the following statements accurately describes the access and characteristics of this logged data?

Answer: A,C,D

Explanation:
Snowflake AI Observability features logging of application traces and Cortex Analyst logs requests to an event table in the Snowflake database. There is a small latency of '1-2 minutes' before these logged requests are visible, making option A correct. The logs include detailed information such as 'Generated SQL' and 'Request and response bodies', which are stored and can be queried, validating option C. The necessary roles for AI Observability, including 'SNOWFLAKE.CORTEX_USER and EVENTS_LOOKUP' , are required for creating and executing runs, which implies they grant access to the generated logs for monitoring, making option D correct. Option B is incorrect as the sources do not mention an automatic 7-day purge for these logs. Option E is incorrect because the documentation includes a subheading 'Querying logs with SQL' for Cortex Analyst administrator monitoring, indicating that direct SQL access is supported.


NEW QUESTION # 99
A data team is deploying a new customer service chatbot using Snowflake Cortex Analyst. To accurately forecast and optimize their costs, the team needs to understand how Cortex Analyst billing works. Which of the following statements accurately describe the cost considerations for Snowflake Cortex Analyst?

Answer: D,E

Explanation:
Option B is correct because Cortex Analyst credit rate usage is based on the number of messages processed, specifically 67 Credits per 1 ,000 messages or 0.067 Credits per message. Option E is correct as only successful responses (HTTP 200) from Cortex Analyst are counted towards the credit usage. Option A is incorrect because the number of tokens in each message does not affect the cost for Cortex Analyst; this is a billing model for other Cortex LLM functions, but not Cortex Analyst. Option C is incorrect; Cortex Analyst runs on Snowflake- managed compute resources as a Serverless Feature, meaning virtual warehouse compute is not directly billed for its operations in the same way as a user-managed warehouse. Option D is incorrect. While Cloud Services compute generally has a 10% daily warehouse cost adjustment, Serverless Features (which include Cortex Analyst) do not contribute to this adjustment.


NEW QUESTION # 100
A data analytics team aims to enhance their understanding of customer feedback stored in a Snowflake table called CUSTOMER_FEEDBACK. This table has a REVIEW_TEXT column containing raw customer comments and a CUSTOMER_SEGMENT column. The team wants to classify each review into predefined categories and then generate a concise summary of all reviews for each customer segment. Which of the following Snowflake Cortex AI functions and approaches should they use?

Answer: A,D,E

Explanation:


NEW QUESTION # 101
A data platform administrator needs to retrieve a consolidated overview of credit consumption for all Snowflake Cortex AI functions (e.g., LLM functions, Document AI, Cortex Search) across their entire account for the past week. They are interested in the aggregated daily credit usage rather than specific token counts per query. Which Snowflake account usage views should the administrator primarily leverage to gather this information?

Answer: A

Explanation:


NEW QUESTION # 102
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