인기자격증1Z0-184-25높은통과율덤프샘플다운시험덤프

여러분은 먼저 우리 Itcertkr사이트에서 제공되는Oracle인증1Z0-184-25시험덤프의 일부분인 데모를 다운받으셔서 체험해보세요. Itcertkr는 여러분이 한번에Oracle인증1Z0-184-25시험을 패스하도록 하겠습니다. 만약Oracle인증1Z0-184-25시험에서 떨어지셨다고 하면 우리는 덤프비용전액 환불입니다.

Oracle 1Z0-184-25 덤프는 Oracle 1Z0-184-25 시험의 모든 문제를 커버하고 있어 시험적중율이 아주 높습니다. Itcertkr는 Paypal과 몇년간의 파트너 관계를 유지하여 왔으므로 신뢰가 가는 안전한 지불방법을 제공해드립니다. Oracle 1Z0-184-25시험탈락시 제품비용 전액환불조치로 고객님의 이익을 보장해드립니다.

>> 1Z0-184-25높은 통과율 덤프샘플 다운 <<

Oracle 1Z0-184-25최신버전 시험덤프자료 - 1Z0-184-25최신 업데이트버전 공부문제

저희는 수많은 IT자격증시험에 도전해보려 하는 IT인사들께 편리를 가져다 드리기 위해 Oracle 1Z0-184-25실제시험 출제유형에 근거하여 가장 퍼펙트한 시험공부가이드를 출시하였습니다. 많은 사이트에서 판매하고 있는 시험자료보다 출중한Itcertkr의 Oracle 1Z0-184-25덤프는 실제시험의 거의 모든 문제를 적중하여 고득점으로 시험에서 한방에 패스하도록 해드립니다. Oracle 1Z0-184-25시험은Itcertkr제품으로 간편하게 도전해보시면 후회없을 것입니다.

최신 Oracle Database 23ai 1Z0-184-25 무료샘플문제 (Q22-Q27):

질문 # 22
Which PL/SQL function converts documents such as PDF, DOC, JSON, XML, or HTML to plain text?

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

정답：B

설명：
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.

질문 # 23
Which SQL function is used to create a vector embedding for a given text string in Oracle Database 23ai?

A. VECTOR_EMBEDDING
B. GENERATE_EMBEDDING
C. CREATE_VECTOR_EMBEDDING
D. EMBED_TEXT

정답：A

설명：
The VECTOR_EMBEDDING function in Oracle Database 23ai generates a vector embedding from input data (e.g., a text string) using a specified model, such as an ONNX model loaded into the database. It's designed for in-database embedding creation, supporting vector search and AI applications. Options A, B, and C (GENERATE_EMBEDDING, CREATE_VECTOR_EMBEDDING, EMBED_TEXT) are not valid SQL functions in 23ai. VECTOR_EMBEDDING integrates seamlessly with the VECTOR data type and is documented as the standard method for embedding generation in SQL queries.

질문 # 24
What is the first step in setting up the practice environment for Select AI?

A. Drop any compartment that does not use OCI Generative AI
B. Optionally create an OCI compartment
C. Create a new user account with elevated privileges
D. Create a policy to enable access to OCI Generative AI

정답：B

설명：
Select AI in Oracle Database 23ai enables natural language queries by integrating with OCI Generative AI services. The first step in setting up the practice environment is to optionally create an OCI compartment (A), which organizes and isolates resources in Oracle Cloud Infrastructure (OCI). This is foundational because subsequent steps-like defining policies or configuring the Autonomous Database-depend on a compartment structure, though an existing compartment can be reused, making it optional. Creating a policy (B) is a subsequent step to grant access to OCIGenerative AI, requiring a compartment first. Dropping compartments (C) is irrelevant and disruptive. Creating a user account (D) is not specified as the initial step in Select AI setup. Oracle's Select AI documentation lists compartment setup as the starting point in OCI configuration.

질문 # 25
What is the primary function of an embedding model in the context of vector search?

A. To store vectors in a structured format for efficient retrieval
B. To execute similarity search operations within a database
C. To define the schema for a vector database
D. To transform text or data into numerical vector representations

정답：D

설명：
An embedding model in the context of vector search, such as those used in Oracle Database 23ai, is fundamentally a machine learning construct (e.g., BERT, SentenceTransformer, or an ONNX model) designed to transform raw data-typically text, but also images or other modalities-into numerical vector representations (C). These vectors, stored in the VECTOR data type, encapsulate semantic meaning in a high-dimensional space where proximity reflects similarity. For instance, the word "cat" might be mapped to a 512-dimensional vector like [0.12, -0.34, ...], where its position relative to "dog" indicates relatedness. This transformation is the linchpin of vector search, enabling mathematical operations like cosine distance to find similar items.
Option A (defining schema) misattributes a database design role to the model; schema is set by DDL (e.g., CREATE TABLE with VECTOR). Option B (executing searches) confuses the model with database functions like VECTOR_DISTANCE, which use the embeddings, not create them. Option D (storing vectors) pertains to the database's storage engine, not the model's function-storage is handled by Oracle's VECTOR type and indexes (e.g., HNSW). The embedding model's role is purely generative, not operational or structural. In practice, Oracle 23ai integrates this via VECTOR_EMBEDDING, which calls the model to produce vectors, underscoring its transformative purpose. Misunderstanding this could lead to conflating data preparation with query execution, a common pitfall for beginners.

질문 # 26
What is a key advantage of using GoldenGate 23ai for managing and distributing vector data for AI applications?

A. Automatic translation of vector embeddings between formats
B. Real-time vector data updates across locations
C. Built-in version control for vector data
D. Specialized vector embedding compression

정답：B

설명：
Oracle GoldenGate 23ai is a real-time data replication and integration tool, extended in 23ai to handle the VECTOR data type for AI applications. Its key advantage (A) is enabling real-time updates of vector data across distributed locations-e.g., replicating VECTOR columns from a primary database in New York to a secondary in London with sub-second latency. This ensures AI models (e.g., for similarity search or RAG) access the latest embeddings as source data (e.g., documents) changes, critical for dynamic environments like customer support systems where new queries demand current context. Imagine a VECTOR column storing embeddings of support tickets; GoldenGate keeps these synchronized across regions, minimizing staleness that could degrade AI responses.
Option B (automatic translation) is fictional; GoldenGate doesn't convert vector formats (e.g., FLOAT32 to INT8)-that's a model or application task. Option C (compression) isn't a GoldenGate feature; compression might occur at the storage layer, but GoldenGate focuses on replication fidelity, not size reduction. Option D (version control) misaligns with GoldenGate's purpose; it ensures data consistency, not historical versioning like Git. Real-time replication (A) stands out, as Oracle's documentation emphasizes GoldenGate's role in keeping vector-driven AI applications globally consistent, a game-changer for distributed AI deployments where latency or inconsistency could disrupt user trust. Without this, static exports (e.g., Data Pump) would lag, undermining real-time AI use cases.

질문 # 27
......

많은 시간과 돈이 필요 없습니다. 30분이란 특별학습가이드로 여러분은Oracle 1Z0-184-25인증시험을 한번에 통과할 수 있습니다, Itcertkr에서Oracle 1Z0-184-25시험자료의 문제와 답이 실제시험의 문제와 답과 아주 비슷한 덤프만 제공합니다.

1Z0-184-25최신버전 시험덤프자료: https://www.itcertkr.com/1Z0-184-25_exam.html

Itcertkr에서는Oracle인증1Z0-184-25시험에 대비한 공부가이드를 발췌하여 IT인사들의 시험공부 고민을 덜어드립니다, 최근 더욱 많은 분들이Oracle인증1Z0-184-25시험에 도전해보려고 합니다, Oracle인증1Z0-184-25시험의자격증은 여러분에 많은 도움이 되리라 믿습니다, Oracle 1Z0-184-25높은 통과율 덤프샘플 다운 자격증을 많이 취득하시면 취직뿐만아니라 승진이나 연봉인상에도 가산점이 되어드릴수 있습니다, Itcertkr연구한 전문Oracle 1Z0-184-25인증시험을 겨냥한 덤프가 아주 많은 인기를 누리고 있습니다, 귀중한 시간절약은 물론이고 한번에 1Z0-184-25시험을 패스함으로 여러분의 발전공간을 넓혀줍니다.

영애의 미간을 통과한 주원의 손가락이 코를 따라 내려왔다, 알겠다, 알겠어, Itcertkr에서는Oracle인증1Z0-184-25시험에 대비한 공부가이드를 발췌하여 IT인사들의 시험공부 고민을 덜어드립니다, 최근 더욱 많은 분들이Oracle인증1Z0-184-25시험에 도전해보려고 합니다.

1Z0-184-25 시험문제집 즉 덤프가 지니고 있는 장점 - Oracle AI Vector Search Professional

Oracle인증1Z0-184-25시험의자격증은 여러분에 많은 도움이 되리라 믿습니다, 자격증을 많이 취득하시면 취직뿐만아니라 승진이나 연봉인상에도 가산점이 되어드릴수 있습니다, Itcertkr연구한 전문Oracle 1Z0-184-25인증시험을 겨냥한 덤프가 아주 많은 인기를 누리고 있습니다.

Ray North Ray North

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인기자격증1Z0-184-25높은통과율덤프샘플다운시험덤프

Oracle 1Z0-184-25최신버전 시험덤프자료 - 1Z0-184-25최신 업데이트버전 공부문제

최신 Oracle Database 23ai 1Z0-184-25 무료샘플문제 (Q22-Q27):

1Z0-184-25 시험문제집 즉 덤프가 지니고 있는 장점 - Oracle AI Vector Search Professional

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