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Snowflake SnowPro® Specialty: Gen AI Certification Exam Sample Questions (Q88-Q93):
NEW QUESTION # 88
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?
Answer: E
Explanation:
Option C is correct. AI_PARSE_DOCUMENT is a Cortex AI SQL function designed to extract text, data, and layout elements from documents with high fidelity, preserving structure like tables, headers, and reading order. For digitally-born contracts where layout preservation is needed, the mode is appropriate. For scanned invoices where only text content is needed without layout, the OCR mode, which extracts text LAYOUT from scanned documents and does not preserve layout, is suitable.
NEW QUESTION # 89
A marketing team is analyzing social media comments using Snowflake and wants to categorize them into predefined campaign sentiments (e.g., 'Positive Campaign Engagement', 'Negative Campaign Feedback', 'Neutral Discussion'). They decide to use the SNOWFLAKE. CORTEX. CLASSIFY TEXT function for this task. Which of the following statements about its usage are correct?
Answer: C,E
Explanation:
Option A is incorrect because both the input string and categories for 'CLASSIFY TEXT are case sensitive, meaning different capitalizations can lead to different results. Option B is incorrect because the argument must contain at least two and at most 100 unique categories. Option C is correct as returns an OBJECT (VARIANT) whose 'label' field specifies the category to which the input prompt belongs. Option D is correct because categories can be simple strings or SQL objects, allowing for a description and examples to be provided, which can improve accuracy. Option E is incorrect because the documentation for 'CLASSIFY _ TEXT does not mention automatic truncation of input text based on a token limit, although LLMs typically have context windows. The source only mentions that for non- plain English text, results may not be what you expect, not that the input would be truncated.
NEW QUESTION # 90
A data application developer is using the Snowflake Cortex COMPLETE function to power a multi-turn conversational AI application. They want to ensure responses are creative but not excessively long, adhere to a specific JSON structure, and are filtered for safety. Given the following SQL query snippet, which statements accurately describe the impact of the specified options?
Answer: A,C,E
Explanation:
Option A is incorrect because a higher temperature, such as 0.8, controls the randomness of the output by influencing which possible token is chosen at each step, resulting in more diverse and random output, not deterministic and focused. Option B is correct because the 'max_tokens' option sets the maximum number of output tokens in the response, and small values can result in truncated responses. Option C is correct because the 'guardrails: TRUE option enables Cortex Guard to filter potentially unsafe and harmful responses from a language model. Option D is correct because AI_COMPLETE Structured Outputs allows you to supply a JSON schema that completion responses must follow, and every model supported by AI_COMPLETE supports structured output. Option E is incorrect because to provide a stateful conversational experience, all previous user prompts and model responses should be passed in the 'prompt_or_history' array, but the number of tokens processed increases for each round, and costs increase proportionally. The 'COMPLETE' function is the older version of 'AI_COMPLETE'.
NEW QUESTION # 91
An administrator has configured the 'CORTEX MODELS ALLOWLIST' parameter to only permit the 'mistral-large? model at the account level. A user with the 'PUBLIC' role, which has been granted 'SNOWFLAKE.CORTEX USER and 'SNOWFLAKE."CORTEX- MODEL-ROLE-LLAMA3.1-70B"' , attempts to execute several 'AI_COMPLETE queries. Which of the following queries will successfully execute?
Answer: B,E
Explanation:
Option A is correct. The query directly references 'MISTRAL-LARGE2', which is explicitly in the account-level 'CORTEX MODELS_ALLOWLIST, so it will succeed. Option B is correct. Snowflake first treats the model name as an identifier for a schema-level model object. The user's role has 'SNOWFLAKE."CORTEX-MODEL-ROLE-LLAMA3.1-70B"' granted, which provides access to the 'LLAMA3.1- 70B' model object in 'SNOWFLAKE.MODELS, regardless of the setting for plain model names. option C is incorrect because 'llama3.1-70b' as a plain model name is not in the 'CORTEX_MODELS_ALLOWLIST. Although the user has access to the model object, a plain string like 'llama3.1-70b' will be looked up in the allowlist after failing to match a model object by that plain name, and the allowlist only has 'MISTRAL-LARGE2'. Option D is incorrect. 'snowflake-arctic' is neither in the 'CORTEX MODELS ALLOWLIST nor does the user have a specific application role granting access to a 'snowflake-arctic' model object. Option E is incorrect because "ALTER ACCOUNT operations can only be performed by the 'ACCOUNTADMIN' role, not typically by a 'PUBLIC' user role, regardless of other grants.
NEW QUESTION # 92
A data analyst is using Snowflake Copilot in Snowsight to generate SQL queries for a new dataset containing customer PII. Which of the following statements accurately describes how Snowflake Copilot operates with respect to data access, governance, and model interaction?
Answer: B
Explanation:
Snowflake Copilot is an LLM-powered assistant that is powered by a model fine-tuned by Snowflake, running securely inside Snowflake Cortex. It ensures that your enterprise data and metadata always stay securely inside Snowflake and fully respects RBAC. Crucially, Snowflake Copilot does not have access to the data inside your tables; it generates responses based on the names of your databases, schemas, tables, and columns, and their data types. Options A and C are incorrect because Copilot does not directly access or transmit customer data. Option D is incorrect as it implies direct data access, which Copilot does not perform. Option E is incorrect because Copilot fully integrates with Snowflake's RBAC policies.
NEW QUESTION # 93
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