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| Section | Weight | Objectives |
|---|---|---|
| Implementing Select AI and AI Vector Search in Autonomous AI Database | 20% | - Determine how AI Vector Search supports GenAI pipelines and RAG - Apply AI Vector Search to combined semantic and business-data search scenarios - Describe Select AI in Autonomous AI Database |
| Working with AI and Vector Foundations | 15% | - Explain vectors, embeddings, and the Oracle VECTOR data type - Apply vector distance and indexing concepts to similarity search needs - Describe AI, AGI, and machine learning foundations |
| Identifying Oracle AI Database 26ai Strategy and Autonomous AI Database Basics | 20% | - Create an Autonomous AI Database Serverless instance for a basic workload - Describe Autonomous AI Database characteristics, offerings, and deployment choices - Explain modern data characteristics and the Oracle AI Database 26ai converged strategy |
| Working with JSON and Graph in Oracle AI Database | 20% | - Distinguish when graph capabilities and Property Graph Views fit a business use case - Describe core graph concepts and graph analytic capabilities - Explain JSON and Oracle AI Database JSON capabilities |
| Building Low-Code Applications and Agentic AI | 10% | - Choose the appropriate Agent Factory capability for a no-code AI agent use case - Describe Oracle APEX as Oracle's low-code platform |
| Using Oracle Database Actions and Data Studio Tools | 15% | - Apply Data Studio capabilities to data discovery, integration, analysis, and sharing tasks - Describe Database Actions and core development tools |
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NEW QUESTION # 34
How can developers access JSON Duality Views?
Answer: C
Explanation:
Developers can access JSON-Relational Duality Views using document-oriented interfaces, including Oracle AI Database API for MongoDB , as well as SQL-based database interfaces. The uploaded source explicitly identifies "MongoDB-compatible APIs or SQL" as correct. Oracle documentation confirms that duality views expose relational table data as JSON documents and that applications can interact with the same underlying data either document-centrically or relationally.
With the MongoDB-compatible API, the duality view can be treated as a document collection by applications using familiar MongoDB drivers and development patterns. At the same time, because the authoritative data remains in Oracle relational tables, SQL and other relational capabilities can operate directly on the same information. This is a primary architectural advantage of JSON-Relational Duality.
No export into a separate document store is necessary; doing so would reintroduce data duplication and synchronization problems that duality views are designed to avoid. Graph visualization is unrelated to document access, and although APEX applications can consume database data, APEX-specific PL/SQL packages are not the principal interface defining duality-view access.
Study Guide reference: Working with JSON and Graph in Oracle AI Database - JSON Duality Views, Oracle AI Database API for MongoDB, SQL access, and unified relational/document development.
NEW QUESTION # 35
What describes the role of the Database Actions menu in Autonomous AI Database?
Answer: D
Explanation:
Database Actions serves as the primary web-based launchpad for built-in Autonomous AI Database tooling.
Oracle describes Database Actions, also known as SQL Developer Web, as an integrated interface containing development, data, administration, monitoring, and download features. From this environment, users can access SQL Worksheet, Data Modeler, REST, JSON tools, Oracle Machine Learning, Graph Studio, Oracle APEX, Data Studio functions, database-user administration, Data Pump, Performance Hub, and other database services.
Its role is therefore broader than any single database technology. Graph Studio is one tool accessible through the environment rather than a replacement for SQL. Network isolation is configured through Autonomous AI Database networking facilities such as private endpoints, not by treating Database Actions itself as a network- access mechanism. Likewise, vector-index settings represent only one narrow area of database functionality and do not define the Database Actions environment. Oracle also documents Data Studio as a feature area accessed through Database Actions, reinforcing the concept of Database Actions as a common launchpad for multiple specialized workspaces. The uploaded question set marks the central built-in-tools location as the correct response.
Study Guide reference: Using Oracle Database Actions and Data Studio Tools - Database Actions Launchpad, development tools, Data Studio, administration, and monitoring.
NEW QUESTION # 36
A data analyst wants to discover data, load it into the platform, and prepare it for later use without leaving the built-in tools. Which workspace fits this task?
Answer: B
Explanation:
Data Studio is the correct built-in workspace because its purpose directly covers data discovery, loading, preparation, transformation, analysis, cataloging, sharing, and related self-service workflows. The uploaded source designates Data Studio as the correct answer. Oracle's current Autonomous AI Database documentation states that Data Studio can be used to load, discover, catalog, transform, analyze, share, enrich, and automate data workflows through a web-based interface.
Data Studio is available through Database Actions and contains specialized tools including Data Load , Catalog , Data Transforms , Data Analysis , and Data Insights . Data Load can ingest or link data from local files, remote databases, cloud storage, and live feeds, while Catalog supports searching, discovering, inspecting, and managing available data assets.
OCI Vault addresses secrets and encryption-key management rather than data preparation.
VECTOR_DISTANCE is an individual SQL function used for vector comparisons, not an integrated analyst workspace. A Property Graph View defines a graph representation over data but likewise does not provide general discovery and loading functionality.
Study Guide reference: Using Oracle Database Actions and Data Studio Tools - Data Studio, Data Load, Catalog, Data Transforms, and self-service data preparation.
NEW QUESTION # 37
A business wants one data platform where semantic similarity, relational consistency, and SQL-based filtering all work together.
Which statement aligns with this design goal?
Answer: D
Explanation:
Comprehensive and Detailed 100 to 150 words of Explanation From Oracle AI Database topics:
Oracle AI Database's converged architecture is designed to keep vectors and conventional business data in the same database so semantic ranking can be combined directly with SQL predicates. Oracle's VECTOR data type enables vector similarity search inside the database, and Oracle explicitly documents combining business- data searches with AI vector similarity search using SQL and the broader converged engine. This preserves transactional consistency and avoids exporting data to a separate vector platform merely to perform semantic retrieval. Options A and C incorrectly separate relational filtering from vector retrieval, while option B incorrectly requires graph modeling. The intended architecture is therefore one database that combines relational filtering, consistency, and vector similarity. This is a core design principle under "Implementing Select AI and AI Vector Search in Autonomous AI Database." Oracle Docs
NEW QUESTION # 38
Which output can Select AI deliver to an application?
Answer: B
Explanation:
Comprehensive and Detailed 100 to 150 words of Explanation From Oracle AI Database topics:
Select AI supports multiple response modes depending on the action requested. With the default runsql action, Oracle generates SQL from the natural-language prompt, executes it, and returns the resulting data. The showsql action returns the generated SQL statement without executing it, while narrate executes the generated query and sends its results to the configured LLM to produce a natural-language description. Oracle additionally supports actions such as explainsql, chat, and summarize. Therefore, an application can receive a database result set, generated SQL, or a narrative response depending on how Select AI is invoked. Graph visualizations, patch-history maintenance recommendations, and automatic JSON export files are not Select AI output modes. This directly aligns with Oracle's Select AI actions and natural-language database interaction capabilities.
NEW QUESTION # 39
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