1Z0-184-25 RELIABLE EXAM SYLLABUS | RELIABLE 1Z0-184-25 EXAM TIPS

1Z0-184-25 Reliable Exam Syllabus | Reliable 1Z0-184-25 Exam Tips

1Z0-184-25 Reliable Exam Syllabus | Reliable 1Z0-184-25 Exam Tips

Blog Article

Tags: 1Z0-184-25 Reliable Exam Syllabus, Reliable 1Z0-184-25 Exam Tips, Exam 1Z0-184-25 Syllabus, Detailed 1Z0-184-25 Study Dumps, Certification 1Z0-184-25 Questions

We assure that you can not only purchase high-quality 1Z0-184-25 prep guide but also gain great courage & trust from us. A lot of online education platform resources need to be provided by the user registration to use after purchase, but it is simple on our website. We provide free demo of 1Z0-184-25 Guide Torrent, you can download any time without registering. Fast delivery—after payment you can receive our 1Z0-184-25 exam torrent no more than 10 minutes, so that you can learn fast and efficiently. What are you waiting for? Just come and buy our 1Z0-184-25 exam questions!

Our materials can make you master the best 1Z0-184-25 questions torrent in the shortest time and save your much time and energy to complete other thing. What most important is that our 1Z0-184-25 study materials can be download, installed and used safe. We can guarantee to you that there no virus in our product. Not only that, we also provide the best service and the best 1Z0-184-25 Exam Torrent to you and we can guarantee that the quality of our product is good. So please take it easy after the purchase and we won’t let your money be wasted.

>> 1Z0-184-25 Reliable Exam Syllabus <<

Reliable 1Z0-184-25 Exam Tips | Exam 1Z0-184-25 Syllabus

You can also trust Lead2Passed Oracle 1Z0-184-25 exam questions and start this journey with complete peace of mind and satisfaction. The Oracle AI Vector Search Professional practice questions are designed and verified by experienced and qualified Oracle AI Vector Search Professional (1Z0-184-25) exam experts. They work collectively and put their expertise to ensure the top standard of Lead2Passed Oracle 1Z0-184-25 Exam Dumps. So we can say that with the Lead2Passed Oracle 1Z0-184-25 exam questions, you will get everything that you need to learn, prepare and pass the difficult Oracle 1Z0-184-25 certification exam with good scores.

Oracle AI Vector Search Professional Sample Questions (Q35-Q40):

NEW QUESTION # 35
Why would you choose to NOT define a specific size for the VECTOR column during development?

  • A. It limits the length of text that can be vectorized
  • B. It restricts the database to a single embedding model
  • C. Different external embedding models produce vectors with varying dimensions and data types
  • D. It impacts the accuracy of similarity searches

Answer: C

Explanation:
In Oracle Database 23ai, a VECTOR column can be defined with a specific size (e.g., VECTOR(512, FLOAT32)) or left unspecified (e.g., VECTOR). Not defining a size (D) provides flexibility during development because different embedding models (e.g., BERT, SentenceTransformer) generate vectors with varying dimensions (e.g., 768, 384) and data types (e.g., FLOAT32, INT8). This avoids locking the schema into one model, allowing experimentation. Accuracy (A) isn't directly impacted by size definition; it depends on the model and metric. A fixed size doesn't restrict the database to one model (B) but requires matching dimensions. Text length (C) affects tokenization, not vector dimensions. Oracle's documentation supports undefined VECTOR columns for flexibility in AI workflows.


NEW QUESTION # 36
Which PL/SQL function converts documents such as PDF, DOC, JSON, XML, or HTML to plain text?

  • A. DBMS_VECTOR_CHAIN.UTL_TO_TEXT
  • B. DBMS_VECTOR_CHAIN.UTL_TO_CHUNKS
  • C. DBMS_VECTOR.TEXT_TO_PLAIN
  • D. DBMS_VECTOR.CONVERT_TO_TEXT

Answer: A

Explanation:
In Oracle Database 23ai, DBMS_VECTOR_CHAIN.UTL_TO_TEXT is the PL/SQL function that converts documents in formats like PDF, DOC, JSON, XML, or HTML into plain text, a key step in preparing data for vectorization in RAG workflows. DBMS_VECTOR.TEXT_TO_PLAIN (A) is not a valid function. DBMS_VECTOR_CHAIN.UTL_TO_CHUNKS (C) splits text into smaller segments, not converts documents. DBMS_VECTOR.CONVERT_TO_TEXT (D) does not exist in the documented packages. UTL_TO_TEXT is part of the DBMS_VECTOR_CHAIN package, designed for vector processing pipelines, and is explicitly noted for document conversion in Oracle's documentation.


NEW QUESTION # 37
What is the correct order of steps for building a RAG application using PL/SQL in Oracle Database 23ai?

  • A. Load Document, Load ONNX Model, Split Text into Chunks, Create Embeddings, VectorizeQuestion, Perform Vector Search, Generate Output
  • B. Load ONNX Model, Vectorize Question, Load Document, Split Text into Chunks, Create Embeddings, Perform Vector Search, Generate Output
  • C. Load Document, Split Text into Chunks, Load ONNX Model, Create Embeddings, Vectorize Question, Perform Vector Search, Generate Output
  • D. Vectorize Question, Load ONNX Model, Load Document, Split Text into Chunks, Create Embeddings, Perform Vector Search, Generate Output

Answer: C

Explanation:
Building a RAG application in Oracle 23ai using PL/SQL follows a logical sequence: (1) Load Document (e.g., via SQL*Loader) into the database; (2) Split Text into Chunks (e.g., DBMS_VECTOR_CHAIN.UTL_TO_CHUNKS) to manage token limits; (3) Load ONNX Model (e.g., via DBMS_VECTOR) for embedding generation; (4) Create Embeddings (e.g., UTL_TO_EMBEDDINGS) for the chunks; (5) Vectorize Question (using the same model) when a query is received; (6) Perform Vector Search (e.g., VECTOR_DISTANCE) to find relevant chunks; (7) Generate Output (e.g., via DBMS_AI with an LLM). Option B matches this flow. A starts with the model prematurely. C prioritizes the question incorrectly. D is close but loads the model too early. Oracle's RAG workflow documentation outlines this document-first approach.


NEW QUESTION # 38
An application needs to fetch the top-3 matching sentences from a dataset of books while ensuring a balance between speed and accuracy. Which query structure should you use?

  • A. Approximate similarity search with the VECTOR_DISTANCE function
  • B. Exact similarity search with Euclidean distance
  • C. A combination of relational filters and similarity search
  • D. Multivector similarity search with approximate fetching and target accuracy

Answer: A

Explanation:
Fetching the top-3 matching sentences requires a similarity search, and balancing speed and accuracy points to approximate nearest neighbor (ANN) techniques. Option A-approximate similarity search with VECTOR_DISTANCE-uses an index (e.g., HNSW, IVF) to quickly find near-matches, ordered by distance (e.g., SELECT sentence, VECTOR_DISTANCE(vector, :query_vector, COSINE) AS score FROM books ORDER BY score FETCH APPROXIMATE 3 ROWS ONLY). The APPROXIMATE clause leverages indexing for speed, with tunable accuracy (e.g., TARGET_ACCURACY), ideal for large datasets where exactness is traded for performance.
Option B (exact search with Euclidean) scans all vectors without indexing, ensuring 100% accuracy but sacrificing speed-impractical for big datasets. Option C ("multivector" search) isn't a standard Oracle 23ai construct; it might imply multiple vectors per row, but lacks clarity and isn't optimal here. Option D (relational filters plus similarity) adds WHERE clauses (e.g., WHERE genre = 'fiction'), useful for scoping but not specified as needed, and doesn't inherently balance speed-accuracy without ANN. Oracle's ANN support in 23ai, via HNSW or IVF withVECTOR_DISTANCE, makes A the practical choice, aligning with real-world RAG use cases where response time matters as much as relevance.


NEW QUESTION # 39
Which Python library is used to vectorize text chunks and the user's question in the following example?
import oracledb
connection = oracledb.connect(user=un, password=pw, dsn=ds)
table_name = "Page"
with connection.cursor() as cursor:
create_table_sql = f"""
CREATE TABLE IF NOT EXISTS {table_name} (
id NUMBER PRIMARY KEY,
payload CLOB CHECK (payload IS JSON),
vector VECTOR
)"""
try:
cursor.execute(create_table_sql)
except oracledb.DatabaseError as e:
raise
connection.autocommit = True
from sentence_transformers import SentenceTransformer
encoder = SentenceTransformer('all-MiniLM-L12-v2')

  • A. json
  • B. oracledb
  • C. sentence_transformers
  • D. oci

Answer: C

Explanation:
In the provided Python code, the sentence_transformers library (A) is imported and used to instantiate a SentenceTransformer object with the 'all-MiniLM-L12-v2' model. This library is designed to vectorize text (e.g., chunks and questions) into embeddings, a common step in RAG applications. The oracledb library (C) handles database connectivity, not vectorization. oci (B) is for OCI service interaction, not text embedding. json (D) processes JSON data, not vectors. The code explicitly uses sentence_transformers for vectorization, consistent with Oracle's examples for external embedding integration.


NEW QUESTION # 40
......

We believe that every customer pays most attention to quality when he is shopping. Only high-quality goods can meet the needs of every customer better. And our 1Z0-184-25 study materials have such high quality, because its hit rate of test questions is extremely high. Perhaps you will find in the examination that a lot of questions you have seen many times in our 1Z0-184-25 Study Materials. In addition, the passing rate is the best test for quality of study materials. And we can be very proud to tell you that the passing rate of our 1Z0-184-25 study materials is almost 100 %.

Reliable 1Z0-184-25 Exam Tips: https://www.lead2passed.com/Oracle/1Z0-184-25-practice-exam-dumps.html

Our 1Z0-184-25 real questions are always aimed at giving you're the best service and experience, So Oracle 1Z0-184-25 exam vce guide makes every exam easy to pass, Oracle 1Z0-184-25 Reliable Exam Syllabus So more than 66300 examinees chose us and got excellent passing score, Oracle 1Z0-184-25 Reliable Exam Syllabus Once you get the certification you may have a higher position and salary, If you are afraid of your qualification exams and have some doubt & questions about our products-- Oracle 1Z0-184-25 latest exam torrent materials we are pleased to serve for you and solve all questions with you any time.

Another critical task is evaluating images—judging not only 1Z0-184-25 their composition and aesthetic value but also the quality of the shots, including focus, lighting, and exposure.

To avoid that, you should adjust only the specific samples containing the sound, Our 1Z0-184-25 Real Questions are always aimed at giving you're the best service and experience.

1Z0-184-25 dumps PDF & 1Z0-184-25 exam guide & 1Z0-184-25 test simulate

So Oracle 1Z0-184-25 exam vce guide makes every exam easy to pass, So more than 66300 examinees chose us and got excellent passing score, Once you get the certification you may have a higher position and salary.

If you are afraid of your qualification exams and have some doubt & questions about our products-- Oracle 1Z0-184-25 latest exam torrent materials we are pleased to serve for you and solve all questions with you any time.

Report this page