Exam GES-C01 Topic 1 Question 285 Discussion

Actual exam question for Snowflake's GES-C01 exam
Question #: 285
Topic #: 1

A data engineering team is setting up an automated pipeline in Snowflake to process call center transcripts. These transcripts, once loaded into a raw table, need to be enriched by extracting specific entities like the customer's name, the primary issue reported, and the proposed resolution. The extracted data must be stored in a structured JSON format in a processed table. The pipeline leverages a SQL task that processes new records from a stream. Which of the following SQL snippets and approaches, utilizing Snowflake Cortex LLM functions, would most effectively extract this information and guarantee a structured JSON output for each transcript?

A. Option A B. Option B C. Option C D. Option D E. Option E

Suggested Answer: C Vote an answer

To guarantee a structured JSON output for entity extraction, (the updated version of 'COMPLETE()') with the response_format' argument and a specified JSON schema is the most effective approach. This mechanism enforces that the LLM's output strictly conforms to the predefined structure, including data types and required fields, significantly reducing the need for post-processing and improving data quality within the pipeline. Option A requires multiple calls and manual JSON assembly, which is less efficient. Option B relies on the LLM's 'natural ability' to generate JSON, which might not be consistently structured without explicit 'response_format' . Option D uses , which is for generating summaries, not structured entity extraction. Option E involves external LLM API calls and Python UDFs, which, while possible, is less direct than using native 'AI_COMPLETE structured outputs within a SQL pipeline in Snowflake Cortex for this specific goal.

by Werner at Sep 28, 2025, 10:09 PM

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