GENERATIVE-AI-ENGINEER-ASSOCIATE · Question #86
A Generative AI Engineer is responsible for developing a chatbot to enable their company's internal HelpDesk Call Center team to more quickly find related tickets and provide resolution. While…
The correct answer is E. transcript Volume. Only the transcript Volume contains the unstructured conversational content needed to semantically match and resolve HelpDesk tickets; the other tables store operational metrics irrelevant to ticket resolution content.
Question
Options
- Bmaintenance_schedule
- Ccall_rep_history
- Etranscript Volume
How the community answered
(23 responses)- B4% (1)
- C13% (3)
- E83% (19)
Why each option
Only the transcript Volume contains the unstructured conversational content needed to semantically match and resolve HelpDesk tickets; the other tables store operational metrics irrelevant to ticket resolution content.
A maintenance_schedule table contains infrastructure scheduling data with no relevance to HelpDesk ticket content or call resolution information.
The call_rep_history Delta table stores performance metrics (call_duration, call_start_time) used for representative KPI calculations, not the conversational or resolution content needed for ticket matching.
The transcript Volume contains *.txt text transcripts of actual support calls, providing the natural language content that can be chunked, embedded, and semantically searched to find related tickets and resolutions - exactly the use case for a RAG-powered HelpDesk chatbot.
Concept tested: RAG data source selection for HelpDesk use case
Source: https://docs.databricks.com/en/generative-ai/retrieval-augmented-generation.html
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