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Snowflake SnowPro® Specialty: Gen AI Certification Sample Questions:

1. 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?

A) To protect sensitive information, Snowflake Copilot transmits sampled PII data to an external LLM for schema understanding before generating SQL.
B) Snowflake Copilot is powered by a fine-tuned model that runs securely inside Snowflake Cortex, leveraging only database/schema/table/column names and data types, ensuring data remains within Snowflake's governance boundary and respects RBAC.
C) While Snowflake Copilot generates SQL based on metadata, the generated SQL queries are executed in an isolated environment that does not respect existing Snowflake RBAC policies.
D) Snowflake Copilot directly accesses and processes the raw data within customer tables to understand its content and generate SQL.
E) Snowflake Copilot requires explicit column-level grants for direct data access, similar to how a human analyst would query specific data points.

2. A business is implementing Snowflake Document AI to process a high volume of scanned legal contracts. The contracts are in PDF format, average 75 pages each, and some are up to 45 MB in size. They need to extract specific clauses, contract dates, and signatory names, including any handwritten elements. The business requires the extracted data to be available for continuous processing within an automated pipeline. Which of the following considerations are critical for successful implementation of this Document AI solution?

A) For continuous processing of new documents, the business needs to create a stream on a stage and a task to automate the execution of the extracting query. Document AI supports processing up to 500 documents in a single query.
B) To train the Document AI model to extract handwritten text and signatures accurately, particularly if readability is low, the business should utilize the 'ocrScore' from the prediction results to flag documents for image quality review or enhancement.
C) When extracting lists of values, such as multiple contract clauses, the Document AI model may initially struggle with complex extractions. It's best practice to train the model with annotations and corrections over a representative dataset to ensure accuracy and correct ordering.
D) Document AI automatically detects page orientation and supports PDF as a file format. The maximum page limit of 125 pages per document and size limit of 50 MB are well within the specifications for these contracts.
E) The primary method for extracting information is This method is exclusively designed for zero-shot extraction, thus fine-tuning is not an option to improve results on specific document types like these contracts.

3. A data team is refining their Cortex Analyst semantic model to improve the accuracy of responses for specific, frequently asked questions and to enable better literal value searches. Consider a semantic model being developed to address these requirements. Which two configurations or features are directly relevant and correctly applied in the semantic model YAML for these purposes?

A) Option A
B) Option B
C) Option E
D) Option D
E) Option C

4. An enterprise is deploying a new RAG application using Snowflake Cortex Search on a large dataset of customer support tickets. The operations team is concerned about managing compute costs and ensuring efficient index refreshes for the Cortex Search Service, which needs to be updated hourly. Which of the following considerations and configurations are relevant for optimizing cost and performance of the Cortex Search Service in this scenario?

A) For optimal performance and cost efficiency, Snowflake recommends using a dedicated warehouse of size no larger than MEDIUM for each Cortex Search Service.
B) For embedding text, selecting a model like

C) CHANGE_TRACKING
D) The
E) The primary cost driver for Cortex Search is the number of search queries executed against the service, with the volume of indexed data (GB/month) having a minimal impact on overall billing.

5. A financial institution uses Snowflake Cortex Analyst with strict role-based access control (RBAC) on their Snowflake-hosted LLMs. The security team has granted specific 'CORTEX-MODEL-ROLE application roles to different analyst teams, ensuring they only access approved models. A new requirement arises to enable Azure OpenAI GPT models for Cortex Analyst to leverage a specific feature. An administrator proceeds to execute:

Which of the following statements accurately describe the implications of this change?

A) Option A
B) Option B
C) Option E
D) Option D
E) Option C

Solutions: