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1Z0-184-25 Real Exam Questions

Oracle AI Vector Search Professional

60 questions available · Page 1 of 6

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Question 1 Single choice

Why would you choose to NOT define a specific size for the VECTOR column during development?

  1. A

    It impacts the accuracy of similarity searches

  2. B

    It restricts the database to a single embedding model

  3. C

    It limits the length of text that can be vectorized

  4. D

    Different external embedding models produce vectors with varying dimensions and data types

Show answer and explanation

Correct answer: D

Question 2 Single choice

How is the security interaction between Autonomous Database and OCI Generative AI managed in the context of Select AI?

  1. A

    By encrypting all communication between the Autonomous Database and OCI Generative AI using
    TLS/SSL protocols

  2. B

    By utilizing Resource Principals, which grant the Autonomous Database instance access to OCI Generative AI without exposing sensitive credentials

  3. C

    By establishing a secure VPN tunnel between the Autonomous Database and OCI Generative AI service

  4. D

    By requiring users to manually enter their OCI API keys each time they execute a natural language query

Show answer and explanation

Correct answer: B

Question 3 Single choice

Which of the following actions will result in an error when using VECTOR_DIMENSION_COUNT() in Oracle Database 23ai?

  1. A

    Providing a vector with a dimensionality that exceeds the specified dimension count

  2. B

    Using a vector with a data type that is not supported by the function

  3. C

    Providing a vector with duplicate values for its components

  4. D

    Calling the function on a vector that has been created with TO_VECTOR()

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Correct answer: B

Question 4 Single choice

When generating vector embeddings outside the database, what is the most suitable option for storing the embeddings for later use?

  1. A

    In a CSV file

  2. B

    In a binary FVEC file with the relational data in a CSV file

  3. C

    In the database as BLOB (Binary Large Object) data

  4. D

    In a dedicated vector database

Show answer and explanation

Correct answer: D

Question 5 Single choice

What is the purpose of the VECTOR_DISTANCE function in Oracle Database 23ai similarity search?

  1. A

    To fetch rows that match exact vector embeddings

  2. B

    To create vector indexes for efficient searches

  3. C

    To group vectors by their exact scores

  4. D

    To calculate the distance between vectors using a specified metric

Show answer and explanation

Correct answer: D

Question 6 Single choice

Which is a characteristic of an approximate similarity search in Oracle Database 23ai?

  1. A

    It compares every vector in the dataset

  2. B

    It trades off accuracy for faster performance

  3. C

    It always guarantees 100% accuracy

  4. D

    It is slower than exact similarity search

Show answer and explanation

Correct answer: B

Question 7 Single choice

Which statement best describes the capability of Oracle Data Pump for handling vector data in thecontext of vector search applications?

  1. A

    Data Pump only exports and imports vector data if the vector embeddings are stored as BLOB (Binary Large Object) data types in the database

  2. B

    Data Pump treats vector embeddings as regular text strings, which can lead to data corruption or loss of precision when transferring vector data for vector search

  3. C

    Data Pump provides native support for exporting and importing tables containing vector data types, facilitating the transfer of vector data for vector search applications

  4. D

    Because of the complexity of vector data, Data Pump requires a specialized plug-in to handle the export and import operations involving vector data types

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Correct answer: C

Question 8 Single choice

What is the primary function of an embedding model in the context of vector search?

  1. A

    To define the schema for a vector database

  2. B

    To execute similarity search operations within a database

  3. C

    To transform text or data into numerical vector representations

  4. D

    To store vectors in a structured format for efficient retrieval

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Correct answer: C

Question 9 Single choice

What happens when querying with an IVF index if you increase the value of the NEIGHBOR_PARTITIONS probes parameter?

  1. A

    The number of centroids decreases

  2. B

    Accuracy decreases

  3. C

    Index creation time is reduced

  4. D

    More partitions are probed, improving accuracy, but also increasing query latency

Show answer and explanation

Correct answer: D

Question 10 Single choice

You are tasked with creating a table to store vector embeddings with the following characteristics: Each vector must have exactly 512 dimensions, and the dimensions should be stored as 32-bitfloating point numbers.

Which SQL statement should you use?

  1. A

    CREATE TABLE vectors (id NUMBER, embedding VECTOR(512))

  2. B

    CREATE TABLE vectors (id NUMBER, embedding VECTOR)

  3. C

    CREATE TABLE vectors (id NUMBER, embedding VECTOR(*, INT8))

  4. D

    CREATE TABLE vectors (id NUMBER, embedding VECTOR(512, FLOAT32))

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Correct answer: D