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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.

Generative AI Application Design

Question

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 creating the GenAI application work breakdown tasks for this project, they realize they need to start planning which data sources (either Unity Catalog volume or Delta table) they could choose for this application. They have collected several candidate data sources for consideration: - call_rep_history: a Delta table with primary keys representative_id, call_id. This table is maintained to calculate representatives' call resolution from fields call_duration and call start_time. - Volume: a Unity Catalog Volume of all recordings as a files, but also a transcript *.wav text transcript as *.txt files. - call_cust_history: a Delta table with primary keys customer_id, cal1_id. This table is maintained to calculate how much internal customers use the HelpDesk to make sure that the charge back model is consistent with actual service use. - call_detail: a Delta table that includes a snapshot of all call details updated hourly. It includes root_cause and resolution fields, but those fields may be empty for calls that are still active. - maintenance_schedule - a Delta table that includes a listing of both HelpDesk application outages as well as planned upcoming maintenance downtimes. They need sources that could add context to best identify ticket root cause and resolution. Which TWO sources do that? (Choose two.) call_cust_history A.

Options

  • Bmaintenance_schedule
  • Ccall_rep_history
  • Etranscript Volume

How the community answered

(23 responses)
  • B
    4% (1)
  • C
    13% (3)
  • E
    83% (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.

Bmaintenance_schedule

A maintenance_schedule table contains infrastructure scheduling data with no relevance to HelpDesk ticket content or call resolution information.

Ccall_rep_history

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.

Etranscript VolumeCorrect

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

Topics

#Data Source Selection#Generative AI Application Design#Contextual Information Retrieval

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