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Databricks GenAI Engineer RAG Application Design Quiz

This quiz evaluates your understanding of Retrieval-Augmented Generation (RAG) application design on Databricks. It covers vector databases, embedding models, LLM integration, retrieval strategies, and production deployment...

Questions: 19 | Attempts: 10 | Last updated: Aug 11, 2026

Sample Question 1
What is the primary purpose of a vector database in a RAG system?

Store and retrieve semantically similar documents using embeddings

Execute SQL queries on structured data

Cache LLM responses for faster inference

Compress large language models for mobile deployment

Sample Question 2
Which embedding model is commonly used in Databricks RAG pipelines?

Text2Vec

BGE (BAAI General Embedding)

PCA-Transformer

FastText-Only

Sample Question 3
In a RAG system, what does the retrieval component do before passing context to the LLM?

Fine-tunes the language model on domain data

Searches for and returns relevant documents from a knowledge base

Translates user queries into multiple languages

Compresses retrieved documents to reduce token count

Databricks Generative AI Engineer Associate Quizzes, Questions & Answers

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