Snowflake SnowPro® Specialty: Gen AI Certification : GES-C01 valid dump

A company is building an enterprise search solution in Snowflake, where user queries are converted into embeddings and then used to find relevant documents from a large corpus. The search logic heavily relies on VECTOR_COSINE_SIMILARITY Which of the following design choices or operational considerations are critical for a robust and efficient implementation using Snowflake's vector capabilities? (Select all that apply)

• A. To keep document embeddings updated efficiently, a
• B. Storing document embeddings in a
• C. When deploying custom embedding models or complex search logic, Snowpark Container Services can host GPU-accelerated environments, while
• D. For improved retrieval quality in RAG scenarios, it is recommended to split text into smaller chunks, ideally no more than 512 tokens, before generating embeddings for subsequent
• E. Bind variables can be used to pass query vector literals securely and efficiently to

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 embedding text, selecting a model like
  
• B. The
  
• C. For optimal performance and cost efficiency, Snowflake recommends using a dedicated warehouse of size no larger than MEDIUM for each Cortex Search Service.
• D. CHANGE_TRACKING
• E. The primary cost driver for Cortex Search is the number of search queries executed against the service, with the volume of indexed data (GBImonth) having a minimal impact on overall billing.

A new ML Engineer, 'data_scientist_role' , has been assigned to a project involving custom machine learning models in Snowflake. They need to gain the necessary permissions to perform the following actions related to Snowflake Model Registry and Snowpark Container Services: 1. Log a custom model into a specified schem a. 2. Deploy that model to an existing Snowpark Container Service compute pool. 3. Call the deployed model for inference using SQL. Which of the following SQL commands grant the 'minimal' required privileges to the for these actions, assuming the compute pool and image repository already exist and are appropriately configured?

• A.
  
• B.
  
• C.
  
• D.
  
• E.
  

A data engineer is working with Snowflake Cortex Analyst to improve its ability to answer natural language questions by precisely identifying product names for filtering. They have decided to integrate a Cortex Search Service with their semantic model to enhance literal search for the 'product_name' dimension. Which of the following configurations within the semantic model's YAML file are valid and effective for this purpose?

• A. Adding a entry to the 'product_name' dimension, including 'literal_column' and ensuring the search service is configured to index the physical column:
  
• B. Including in the semantic model's 'metrics' section, referencing 'product_name'.
• C. Setting true' for the 'product_name' dimension and providing an exhaustive list of to restrict the model to only those values.
• D. Adding a 'cortex_search_service' entry to the 'product_name' dimension with only the 'service' field:
  
• E. Only specifying 'sample_valueS for the 'product_name' dimension without a entry.

A security administrator is implementing strict model access controls for Snowflake Cortex LLM functions, including those accessed via the Cortex REST API. By default, the 'SNOWFLAKE.CORTEX USER' database role is granted to the 'PUBLIC' role, allowing all users to call Cortex AI functions. To enforce a more restrictive access policy, the administrator revokes 'SNOWFLAKE.CORTEX USER from 'PUBLIC'. Which of the following actions must the administrator take to ensure specific roles can 'still' make Cortex REST API requests, and what are the implications?

• A. Only the role can make cortex REST API calls after revoking 'SNOWFLAKE.CORTEX_USER from 'PUBLIC', as this role inherently bypasses all other access controls.
• B. The 'SNOWFLAKE.CORTEX USER database role must be granted directly to individual users who need access, as it cannot be granted to other account roles.
• C. The 'SNOWFLAKE.CORTEX USER database role must be granted to the specific account roles, and then these account roles must be granted to users. Additionally, the account parameter can be used to restrict which models are accessible.
• D. Access for Cortex REST API is managed independently of database roles; a separate REST API key must be provisioned for each user or application.
• E. The from 'SNOWFLAKCORTEX USER database role is only required for SQL functions, not for the Cortex REST API, so no further action is needed after revoking 'PUBLIC for REST API access.