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Snowflake SnowPro® Specialty: Gen AI Certification Exam Sample Questions (Q103-Q108):

NEW QUESTION # 103
A data analyst needs to use SNOWFLAKE. CORTEX. EXTRACT_ANSWER to streamline information retrieval from various contract documents. They are new to Cortex functions and want to understand access requirements and optimal usage. Which of the following statements about using SNOWFLAKE .CORTEX. EXTRACT_ANSWER are correct?

Answer: A,B,C

Explanation:
Option A is correct because users must use a role that has been granted the 'SNOWFLAKE.CORTEX USER database role to access EXTRACT_ANSWER and other Cortex AI functions. Option B is correct because for optimal performance and accurate responses, it is recommended to use plain English text for input and categories, and questions should be specific and ask for a single value. Option C is incorrect; EXTRACT_ANSWER would typically raise an error if an operation cannot be performed. The 'TRY_COMPLETE function is specifically designed to return 'NULL' instead of an error in such cases. Option D is incorrect; 'EXTRACT ANSWER is an older version of this function, and 'AI_EXTRACT' is the latest version, which supports additional capabilities like image and multi-language extraction. Option E is correct; EXTRACT ANSWER can be called on a table column, enabling efficient batch processing of multiple documents or text entries. This is a common pattern for integrating Cortex functions into data pipelines.


NEW QUESTION # 104
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?

Answer: D

Explanation:
Option B is correct. Snowflake Cortex functions, including SNOWFLAKE .CORTEX. SENTIMENT, do not support dynamic tables. This is a fundamental limitation that would cause the CREATE DYNAMIC TABLE statement to fail when trying to incorporate a Cortex function. While the 'CORTEX_USER role is indeed required for calling Cortex AI functions, the direct failure in this scenario is due to the incompatibility with dynamic tables. Option C is incorrect as there's no specified TARGET_LAG' limitation. Option D is incorrect; Snowflake recommends using a smaller warehouse (no larger than MEDIUM) for Cortex functions, but a Snowpark-optimized warehouse is not a strict requirement, and larger warehouses do not increase performance. Option E is incorrect because 'SENTIMENT is designed for English-language input text, and non-English text would likely lead to unexpected or inaccurate results, not a direct failure of the function call itself.


NEW QUESTION # 105
A business analyst is using a Cortex Analyst-powered conversational application to query structured data in Snowflake. They initially ask, 'What was the total profit from California last quarter?' and then follow up with, 'What about New York?' The application successfully provides accurate answers to both questions. Which of the following statements explain how Cortex Analyst supports this multi-turn conversational experience and maintains accuracy? (Select all that apply)

Answer: A,B,D

Explanation:
Option A is incorrect. Cortex Analyst does not simply pass the full, verbatim history of all previous prompts and responses to every subsequent LLM call. This 'primitive way' could lead to longer inference times, more non-determinism, and degraded performance due to multitasking. Instead, it uses an LLM summarization agent to manage context. Option B is correct. Cortex Analyst supports multi-turn conversations by recognizing follow-up questions and using an LLM summarization agent (such as Llama 3.1 70B, which showed high accuracy in this role) to retrieve context from the conversation history and reframe the current-turn question. Option C is correct. The Verified Query Repository (VQR) is a collection of pre-verified questions and corresponding SQL queries that helps improve the accuracy and trustworthiness of Cortex Analyst's results by using relevant SQL queries for similar questions. Option D is incorrect. While semantic search over sample values can improve literal search for Cortex Analyst, it is not the primary mechanism for managing the context of multi-turn conversations. Context management relies on an LLM summarization agent. Option E is correct. Semantic models, captured in lightweight YAML files, are critical for Cortex Analyst. They provide richer semantic information than basic database schemas, bridging the gap between business user language and technical database definitions, which is essential for accurate text-to-SQL conversions in both initial and follow-up queries.


NEW QUESTION # 106
An organization is implementing a two-tier LLM access control strategy in Snowflake. First, common models like 'mistral-7b' and 'llama3.1-8b' need to be broadly accessible to all users granted the 'SNOWFLAKE-CORTEX USER database role. Second, a specialized data science team, using the ANALYST ROLE', requires exclusive access to the higher-capability 'claude-3-5- sonnet' model, which should NOT be generally available through the broad access mechanism. Which set of SQL commands, executed by the 'ACCOUNTADMIN" role, correctly establishes this access control strategy?

Answer: D

Explanation:
Option A is correct. This sequence first uses 'ALTER ACCOUNT SET CORTEX MODELS_ALLOWLIST to make 'mistral-7b' and broadly available by their plain names to any user with The call ensures these changes are applied. Then, it grants the specific application role 'SNOWFLAKE."CORTEX-MODEL-ROLE-CLAUDE-3-5-SONNET"' directly to , providing exclusive access to that model without adding it to the general allowlist. Option B is incorrect because adding 'claude-3-5-sonnet' to the account-level would make it generally available, violating the requirement for exclusive access. Option C is incorrect because granting individual application roles to 'PUBLIC' for 'mistral-7b' and is not the method described for making them broadly accessible via an account parameter (allowlist). While it provides access, it doesn't align with the 'broadly accessible...via a Snowflake account parameter' part of the requirement. Option D is incorrect as 'ALTER ACCOUNT UNSET removes the broad access for 'mistral-7b' and Additionally, direct 'GRANT USAGE ON MODELS is not the primary mechanism for controlling access to base Cortex models; rather, application roles are used. Option E is incorrect because the 'ALTER ACCOUNT command for 'CORTEX MODELS_ALLOWLIST can only be executed by the 'ACCOUNTADMIN' role, not 'SECURITYADMIN'.


NEW QUESTION # 107
A Data Engineer has successfully deployed a Document AI model build named 'expense reports' to extract 'total amount' and approver signature' from digital expense reports. They observe that sometimes the 'approver signature' is not present in a document, or certain table cells are intentionally left blank in other document types processed by Document AI. They also want to automate the ingestion and processing of new expense reports. Regarding the '!PREDICT' method's JSON output when 'approver signature' is missing or a table cell is empty, and the recommended Snowflake features for continuously processing new documents, which statements are true?

Answer: A,C

Explanation:
Option B is correct because if a table cell is empty or if the Document AI model does not find an answer in the document, it will not return a 'value' key. However, it will still return the 'score' key, indicating its confidence that the cell is empty or that the answer is not present. Option C is correct as creating document processing pipelines with Document AI typically involves setting up a stream on a stage to capture new documents and a task that then calls the '!PREDICT method to process these new documents automatically. Option A is incorrect; the 'value' key is omitted, not set to 'null'. Option D is incorrect because the 'value' key is omitted entirely, not set to an empty string. Option E is incorrect because Snowflake Cortex functions, including Document AI's '!PREDICT method, do not currently support dynamic tables.


NEW QUESTION # 108
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