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Snowflake GES-C01 Exam Syllabus Topics:

Snowflake SnowPro® Specialty: Gen AI Certification Sample Questions:

1. A data application developer is tasked with building a multi-turn conversational AI application using Streamlit in Snowflake (SiS) that leverages the COMPLETE (SNOWFLAKE. CORTEX) LLM function. To ensure the conversation flows naturally and the LLM maintains context from previous interactions, which of the following is the most appropriate method for handling and passing the conversation history?

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

2. A development team is preparing to deploy a new Retrieval-Augmented Generation (RAG) application written in Python. They intend to use Snowflake AI Observability with the TruLens SDK to capture detailed logs and traces for debugging and performance analysis. Which of the following configurations are essential prerequisites for enabling this logging capability effectively?

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

3. A team of data application developers is leveraging Snowflake Copilot to streamline the creation of analytical SQL queries within their Streamlit in Snowflake application. They observe that Copilot sometimes struggles with complex joins or provides suboptimal queries when dealing with a newly integrated, deeply nested dataset. Based on Snowflake's best practices and known limitations, which actions or considerations would help improve Copilot's performance in this scenario?

A) Ensure that a database and schema are explicitly selected for the current session, and that column names are meaningful, to provide Copilot with better context for query generation.
B) Implement curated views with descriptive and easy-to-understand names for views and columns, appropriate data types, and pre-define common/complex joins to simplify the underlying schema for Copilot.
C) Enable the CORTEX_MODELS_ALLOWLIST parameter to restrict Copilot to only use the largest available LLMs, thereby guaranteeing higher accuracy for complex queries.
D) Break down complex requests into simpler, multi-turn questions, as Copilot is designed to build complex queries through conversational refinement and follow-up questions.
E) Grant Copilot direct access to the raw data using ACCOUNTADMIN privileges, allowing it to infer schema relationships more effectively from data content.

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) The
B) For embedding text, selecting a model like

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) 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.
E) CHANGE_TRACKING

5. A data engineer is integrating SNOWFLAKE. CORTEX. CLASSIFY_TEXT into an automated data pipeline that uses dynamic tables to process and transform streaming text dat a. They have ensured that the service account used has been granted the necessary SNOWFLAKE. CORTEX_USER database role. After deploying the pipeline, they consistently receive an error whenever CLASSIFY_TEXT is invoked. Which of the following is the most likely cause of the error encountered by the data engineer?

A) The role used by the data engineer, despite having 'SNOWFLAKE.CORTEX_USER, lacks the fundamental 'USAGE privilege on the database where the text data is stored.
B) Snowflake Cortex functions, including 'CLASSIFY_TEXT , currently do not support integration with dynamic tables within data pipelines.
C) The input text being processed by 'CLASSIFY _ TEXT includes extensive non-plain English content, such as code blocks, which causes the function to fail with an error.
D) The array contains more than 100 unique categories, exceeding the maximum allowed limit for the function.
E) The 'task_description' provided in the optional arguments for 'CLASSIFY_TEXT exceeds the recommended length of approximately 50 words, leading to a validation error.

Solutions: