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Snowflake SnowPro® Specialty: Gen AI Certification Exam Sample Questions (Q109-Q114):
NEW QUESTION # 109
Answer: C
Explanation:
Option D is correct. All the mentioned Snowflake Cortex AI functions , , 'SNOWFLAKE.CORTEX.COMPLETE) are designed to operate within Snowflake's governance boundary under default configurations. uses Snowflake's proprietary Arctic-TILT model for document extraction, keeping data within the platform. Snowflake Cortex AI functions, including embedding and completion models like 'mistral-large? , are fully hosted and managed by Snowflake, ensuring data remains secure and in place. While REGION' allows processing in a different region, user inputs and outputs are not stored or cached, maintaining data within Snowflake's overall control. Therefore, no data egress to a third-party LLM provider occurs in these steps. Options A, B, and C are incorrect as they contradict the principle of Snowflake-hosted and managed AI features. Option E is incorrect because the 'CORTEX MODELS ALLOWLIST restricts which models can be used, but it does not dictate data egress, as the allowed models are still Snowflake-hosted.
NEW QUESTION # 110
A company is planning to process a large volume of legal documents to generate summaries using SNOWFLAKE. CORTEX. SUMMARIZE. Given the scale, they are acutely focused on managing costs and optimizing performance. Which of the following statements are true regarding the cost and performance characteristics of using SNOWFLAKE. CORTEX. SUMMARIZE? (Select all that apply)
Answer: A,C
Explanation:
Options B and D are correct. - is correct": For 'SUMMARIZE, Snowflake adds an internal prompt to the input text in order to generate the response, which results in a higher input token count for billing than the raw text provided. - is correct'': The cost for the Summarize' function is 0.10 Credits per one million Tokens processed. -A is incorrect: For functions that generate new text in the response, such as 'SUMMARIZE' , both input and output tokens are billable. - C is incorrect: Snowflake recommends executing queries that call a Snowflake Cortex AISQL function, including SUMMARIZE , with a smaller warehouse (no larger than MEDIUM), as larger warehouses do not increase performance for these operations. - E is incorrect: The context window for the Snowflake managed model from the 'SUMMARIZE function is 32,000 tokens, not 4,096 tokens.
NEW QUESTION # 111
A data engineer is designing an automated data pipeline in Snowflake to process incoming customer feedback documents. The pipeline needs to perform the following steps: 1. Extract the overall sentiment from the feedback text. 2. Generate a concise summary of each feedback document. 3. Extract key entities (e.g., product, issue, customer name) into a structured JSON format using a powerful LLM, ensuring adherence to a predefined schema and graceful error handling. Which of the following Snowflake Cortex features and best practices should the data engineer leverage to build this robust AI-infused pipeline?
Answer: A,C,E
Explanation:
NEW QUESTION # 112
A global marketing team uses Snowflake to manage customer feedback in various languages. They need to translate customer reviews from German ("de") into English ("en") for analysis. The reviews are stored in a table named 'CUSTOMER REVIEWS' in a column called 'REVIEW TEXT'. Which of the following SQL statements correctly applies the 'SNOWFLAKE.CORTEX.TRANSLATE function and what is the expected return type for the translated text?
Answer: E
Explanation:
Option B is correct. The 'SNOWFLAKE.CORTEX.TRANSLATE function takes three arguments: the text to be translated, the source language, and the target language. It returns a STRING value containing the translated text. Option A includes an unsupported 'high_accuracy' option and claims an incorrect return type. Option C uses an incorrect syntax and claims an incorrect return type. Option D uses an incorrect number of arguments. Option E claims an incorrect return type.
NEW QUESTION # 113
A global enterprise has Snowflake accounts in various regions, including a US East (Ohio) account where a critical application is deployed. They need to use AI_COMPLETE with the claude-3-5-sonnet model for real-time customer support, but this model is not natively available in US East (Ohio) for direct AI_COMPLETE usage. The Snowflake administrator considers enabling cross-region inference. Which statements accurately reflect the considerations and characteristics of cross-region inference in Snowflake Cortex?
Answer: A,E
Explanation:
Option B is correct because setting the parameter to 'ANY_REGION' enables inference requests to be CORTEX_ENABLED_CROS_ REGION processed in a different region from the default, thereby allowing access to models not natively supported in the local region. For example, claude- 3 - 5- sonnet is available in AWS US East 1 (N. Virginia), which could be accessed from US East (Ohio) via cross-region inference. Option C is 3-5 -sonnet correct as cross-region inference is explicitly not supported in U.S. SnowGov regions for either inbound or outbound inference requests. Option A is incorrect because user inputs, service generated prompts, and outputs are not stored or cached during cross-region inference. Option D is incorrect; latency depends on the cloud provider infrastructure and network status, and testing is recommended. Option E is incorrect because CORTEX_ENABLED_CROSS_REGION is an account-level parameter, not a session parameter.
NEW QUESTION # 114
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