Online 1Z0-184-25 Practice Test

Question 1

How does an application use vector similarity search to retrieve relevant information from a database, and how is this information then integrated into the generation process?

Options :

A :

Encodes the question and database chunks into vectors, finds the most similar using cosine similarity, and includes them in the LLM prompt

B : Trains a separate LLM on the database and uses it to answer, ignoring the general LLM

C : Converts the question to keywords, searches for matches, and inserts the text into the response

D : Clusters similar text chunks and randomly selects one from the most relevant cluster

Answer: A

Question 2

What is the purpose of the Vector Pool in Oracle Database 23ai?

Options :

A : To manage database partitioning

B : To store HNSW vector indexes and IVF index metadata

C : To enable longer SQL execution

D : To store non-vector data types

Answer: B

Question 3

How can vector data be manipulated within an Oracle Database using Data Manipulation Language (DML)?

Options :

A : Insertion only

B : Insertion, updates, deletion, and loading

C : Insertion and updates

D : Insertion, updates, and deletion

Answer: B

Question 4

Multi-Vector Similarity Search is typically used for:

Options :

A : Exact vector matching

B : Single-vector comparisons

C : Multi-document search

D : Image recognition

Answer: C

Question 5

How are vectqr embeddings stored in Oracle Database 23ai?

Options :

A : They are stored in a separate, specialized vector database.

B : They are not stored; they are only used for querying.

C : By creating columns with the VECTOR data type in relational tables.

D : They are appended as metadata to existing data files.

Answer: B

EXPERTY DESIGNED 1Z0-184-25 PRACTICE TEST