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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Architecture and Best Practices | 10-15% | - Cost management strategies - Security and privacy considerations - Monitoring and evaluation frameworks - LLM pipeline architecture design - Performance optimization techniques |
| Topic 2: Cortex Analyst and Semantic Layer | 20-25% | - Business logic implementation in semantic models - Performance tuning for analytical queries - Semantic model design and configuration - Text-to-SQL translation and optimization |
| Topic 3: Data Preparation for Gen AI | 15-20% | - Vector stores and embeddings in Snowflake - Unstructured data handling - Data governance for AI workloads - Document processing and chunking strategies |
| Topic 4: Snowflake Cortex AI Capabilities | 25-30% | - Secure data handling in AI workflows - COMPLETE function usage and parameters - Model selection and cost optimization - Cortex AI functions and features - Snowflake Copilot integration |
| Topic 5: Generative AI Fundamentals and Concepts | 20-25% | - Fine-tuning vs. retrieval approaches - Vector embeddings and similarity search - Prompt engineering principles - LLM fundamentals and architectures - Retrieval-Augmented Generation (RAG) concepts |
A Gen AI specialist is tasked with creating a Snowflake Cortex Search Service to power a Retrieval Augmented Generation (RAG) application for customer support transcripts. The goal is to allow semantic search over the 'transcript_text' column, filter results by 'region' and , and leverage a multilingual embedding model for high-quality results. The service should be created in the 'cortex_search_db.serviceS schema and use as the warehouse. Which of the following SQL commands correctly creates such a Cortex Search Service, assuming 'support_transcripts' is the source table and change tracking is enabled?





Correct Answer: A 🗳️
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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?
Correct Answer: A,E 🗳️
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A data engineering team is building an automated pipeline in Snowflake to process customer reviews. They need to use AI_COMPLETE to extract specific details like product, sentiment, and issue type, and store them in a strictly defined JSON format for seamless downstream integration. They aim to maximize the accuracy of the structured output and manage potential model limitations. Which statements accurately reflect the best practices and characteristics when using AI_COMPLETE with structured outputs for this scenario?
Correct Answer: A,C,E 🗳️
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A data engineering team is setting up an automated pipeline to extract information from new invoices using Document AI. They've created a database and schema Cinvoice_db.invoice_schema') and a Document AI model build They then created an internal stage for documents. When they attempt to run the method on documents uploaded to 'invoice_stage' , they consistently receive the following error:
Given this error message, which 'corrective SQL command' addresses the most likely misconfiguration of the 'invoice_stage' to allow Document AI processing?





Correct Answer: C 🗳️
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A developer has successfully created a Cortex Search Service named transcript _ search service within cortex_search_db. services based on customer support transcripts. They now need to query this service to find support tickets related to 'internet issues' specifically from the 'North America' region, and they only want the single most relevant result. Which of the following SQL commands correctly performs this query?
Correct Answer: B 🗳️
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