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| Section | Objectives |
|---|---|
| Topic 1: Using Oracle Database Actions and Data Studio Tools | - Describe Database Actions and core development tools - Apply Data Studio capabilities to data discovery, integration, analysis, and sharing tasks |
| Topic 2: Working with AI and Vector Foundations | - Describe AI, AGI, and machine learning foundations - Explain vectors, embeddings, and the Oracle VECTOR data type - Apply vector distance and indexing concepts to similarity search needs |
| Topic 3: Building Low-Code Applications and Agentic AI | - Describe Oracle APEX as Oracle's low-code platform - Choose the appropriate Agent Factory capability for a no-code AI agent use case |
| Topic 4: Working with JSON and Graph in Oracle AI Database | - Explain JSON and Oracle AI Database JSON capabilities - Describe core graph concepts and graph analytic capabilities - Distinguish when graph capabilities and Property Graph Views fit a business use case |
| Topic 5: Implementing Select AI and AI Vector Search in Autonomous AI Database | - Apply AI Vector Search to combined semantic and business-data search scenarios - Determine how AI Vector Search supports GenAI pipelines and RAG - Describe Select AI in Autonomous AI Database |
| Topic 6: Identifying Oracle AI Database 26ai Strategy and Autonomous AI Database Basics | - Describe Autonomous AI Database characteristics, offerings, and deployment choices - Explain modern data characteristics and the Oracle AI Database 26ai converged strategy - Create an Autonomous AI Database Serverless instance for a basic workload |
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質問 # 45
What is OSON in Oracle AI Database JSON support?
正解：D
解説：
OSON is Oracle's optimized binary representation for JSON data. Oracle AI Database uses OSON as the native storage representation of the SQL JSON data type. Unlike textual JSON stored in VARCHAR2, CLOB, or BLOB values, native JSON data does not need to be repeatedly parsed from character representation for common processing operations. Oracle states that OSON is optimized for fast query and update operations in both the Oracle AI Database server and supported database clients.
The practical advantage is that applications retain JSON's flexible document model while gaining database- native processing efficiency, SQL integration, indexing capabilities, and transactional control. OSON therefore concerns the physical/optimized representation of JSON data, not the operational scheduling of JSON collections or the visualization of graph structures. It is also unrelated to the SQL Worksheet, which is a Database Actions development interface for executing SQL and PL/SQL. The uploaded question explicitly identifies "An optimized binary format for JSON storage" as the correct answer.
Study Guide reference: Working with JSON and Graph in Oracle AI Database - native JSON data type, OSON binary JSON representation, JSON query and update processing.
質問 # 46
A business team wants to launch a no-code AI agent quickly. They prefer to start from a ready-made option and later refine the publishing workflow. Which Private Agent Factory capability path fits this need?
正解：A
解説：
Oracle AI Database Private Agent Factory is explicitly designed as a no-code environment for rapidly building, testing, and deploying intelligent agents. Oracle documents that Agent Factory supports pre-built agents, custom-built agents, and end-to-end workflows and includes curated agentic templates intended to accelerate implementation. Starting from one of these ready-made assets minimizes initial design work and is therefore the strongest match for a business team that prioritizes rapid deployment.
If additional customization becomes necessary, Agent Builder provides a visual no-code environment for constructing and refining agents and workflows from modular components. Oracle describes capabilities including drag-and-drop workflow construction, data connectors, LLM integration, APIs, custom agent creation, multi-agent orchestration, and reusable templates. This establishes a logical progression: begin with a pre-built agent/template to obtain functionality quickly, then move into Agent Builder when deeper customization or workflow tailoring is required. Starting from a completely blank agent would unnecessarily increase implementation effort, while a prompt-only prototype bypasses Agent Factory's governed agent capabilities. The source question likewise identifies the pre-built-to-Agent-Builder path as correct.
Study Guide reference: Building Low-Code Applications and Agentic AI - Private Agent Factory, pre-built agents, templates, and Agent Builder.
質問 # 47
A team needs faster similarity search at scale and accepts approximate top-K results. Which feature should they use?
正解：D
質問 # 48
Which offering is positioned for JSON-centric workloads and includes Oracle Database API for MongoDB?
正解：D
解説：
Autonomous AI JSON Database is the Oracle Autonomous AI Database offering specifically optimized for document-centric and JSON-centric application workloads. Oracle documentation identifies Autonomous AI JSON Database as optimized for JSON document workloads while retaining the underlying converged capabilities of Oracle AI Database. It supports NoSQL-style access patterns while still permitting applications and administrators to use SQL against the same underlying information.
A key capability is Oracle AI Database API for MongoDB. This interface enables applications to connect to Autonomous AI Database using familiar MongoDB drivers and tools. Oracle translates MongoDB-compatible operations so developers with MongoDB development experience can work with collections of JSON documents residing in Oracle AI Database. The same database can also expose those documents through SQL, PL/SQL, SODA, and other Oracle interfaces.
Autonomous AI Transaction Processing supports mixed and transactional application workloads but is not the specifically positioned JSON-centric offering in this question. Autonomous AI Lakehouse targets analytical and lakehouse-oriented workloads, while Oracle APEX Service is a low-code application platform rather than the JSON database workload type itself. Therefore, Autonomous AI JSON Database is the precise match. The uploaded question set also marks option C as correct.
Study Guide reference: Working with JSON and Graph in Oracle AI Database - Autonomous AI JSON Database and Oracle AI Database API for MongoDB.
質問 # 49
How is Oracle APEX described?
正解：A
解説：
Oracle APEX is Oracle's low-code application development platform , making option C correct. The uploaded source explicitly identifies this characterization. Oracle's current documentation defines APEX as a complete low-code platform for rapidly building secure, scalable enterprise applications. Developers work primarily through the browser-based App Builder and configure declarative components, pages, features, and data sources rather than manually writing the entire application stack.
APEX is built as part of Oracle Database and provides direct access to Oracle Database data. Its model-driven architecture allows developers to use declarative metadata for common application functionality while retaining SQL, PL/SQL, JavaScript, REST, and other extension mechanisms when custom logic is necessary.
The incorrect options describe entirely different Oracle technologies. Graph analytics and property graphs are Oracle Database graph capabilities, not the definition of APEX. Encryption-key lifecycle management belongs to database security and services such as OCI Vault. Oracle's optimized binary representation for JSON storage is OSON.
The exam-level distinction is therefore direct: APEX addresses rapid application creation, especially data- centric enterprise applications, through a browser-based low-code development model tightly integrated with Oracle Database.
Study Guide reference: Building Low-Code Applications and Agentic AI - Oracle APEX, low-code development, App Builder, and database-driven applications.
質問 # 50
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