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| Section | Weight | Objectives |
|---|---|---|
| Oracle Machine Learning and AI Integration | ~15% | - Oracle Data Studio and visualization - In-database machine learning algorithms - AI agents and LLM integration |
| MySQL HeatWave and NoSQL Services | ~11% | - Oracle NoSQL Database features and use cases - MySQL HeatWave architecture and analytics |
| Data Management and Oracle Data Platform Overview | ~11% | - Oracle Data Strategy and multi-cloud deployment models - Modern data platform value and architecture - Data management concepts and data types |
| Oracle Database Services โ Exadata, DBCS, and Engineered Systems | ~11% | - Database Cloud Service (DBCS) characteristics - Exadata architecture and features |
| Converged Database โ Multi-Model and AI Capabilities | ~15% | - Oracle AI Vector Search concepts - JSON, Graph, Spatial, and key-value data support - Select AI and natural language querying |
| Security, Resilience, and Cloud Integration | ~21% | - Cloud-native database services and deployment strategies - High availability, backup, and disaster recovery - Database security architectures and data protection |
| Autonomous AI Database and Tools | ~16% | - Shared vs dedicated infrastructure - Core features of Autonomous AI Database - Built-in management and query tools |
>> Questions 1z0-1195-26 Pdf <<
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NEW QUESTION # 12
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: B
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 # 13
Which set of tools is specifically highlighted as available from Database Actions?
Answer: C
Explanation:
The Database Actions environment specifically includes SQL, Data Modeler, REST, JSON, Oracle Machine Learning, and Oracle APEX , making option C correct. The uploaded assessment identifies the same tool set. Oracle's current Autonomous AI Database documentation describes Database Actions as a web- based interface for development, data tooling, administration, and monitoring. Its Development area includes SQL, Data Modeler, REST, JSON, Charts, Scheduling, Oracle Machine Learning, Spatial Studio, Graph Studio, and Oracle APEX.
SQL provides the browser-based worksheet for SQL and PL/SQL execution. Data Modeler supports database modeling and diagramming. REST provides tools for database REST services and APIs. JSON provides facilities for working with JSON collections and documents. Oracle Machine Learning exposes integrated ML development capabilities, while APEX launches Oracle's low-code application-development environment.
Oracle's Machine Learning documentation likewise identifies Database Actions as the entry point for Oracle Machine Learning.
The remaining choices largely describe OCI infrastructure or security-management services rather than Database Actions development tools. Compute, block storage, load balancing, IAM, billing, private endpoints, and Vault are managed elsewhere in OCI.
Study Guide reference: Using Oracle Database Actions and Data Studio Tools - Database Actions Launchpad and Development tools.
NEW QUESTION # 14
What does a JSON Duality View enable?
Answer: C
Explanation:
A JSON-Relational Duality View allows applications to work with relationally stored information as JSON documents without maintaining a separate document-store copy. The uploaded source identifies this exact capability as the correct answer. Oracle AI Database documentation confirms that a duality view maps relational table data to hierarchical JSON documents that are materialized on demand rather than separately stored. Applications can therefore access and, when permitted, modify the same underlying information either through relational tables or through its document representation.
This architecture preserves relational advantages such as normalization, integrity constraints, SQL processing, and transactional consistency while giving document-oriented applications a natural JSON interface. A change made through an updatable JSON document is reflected in the underlying relational data, and relational changes are correspondingly visible through the duality view.
The feature does not eliminate SQL, transform property graphs into vector indexes, or require synchronization with an independent document database. Oracle specifically positions JSON-Relational Duality as a mechanism for combining relational and document development models around one authoritative data representation.
Study Guide reference: Working with JSON and Graph in Oracle AI Database - JSON-Relational Duality Views, relational storage, and document-oriented access.
NEW QUESTION # 15
In a property graph, what are vertices and edges?
Answer: B
NEW QUESTION # 16
A project team wants a built-in workspace to analyze data assets and support sharing or collaboration after preparation work is complete.
Which choice fits that requirement?
Answer: D
Explanation:
Comprehensive and Detailed 100 to 150 words of Explanation From Oracle AI Database topics:
Data Studio is the correct choice because Oracle positions it as the integrated, web-based data workspace inside Database Actions for loading, discovering, cataloging, transforming, analyzing, sharing, enriching, and automating data workflows. Its Data Analysis capability supports reports and visual analysis, while Data Share and Data Marketplace support governed distribution and collaboration after data preparation. SQL Worksheet is primarily for SQL and PL/SQL execution; Database Users is for user administration; and Private Endpoint configuration is a networking control, not a data-analysis workspace. Therefore, a team that needs to continue from prepared data into analysis and sharing should use Data Studio. This maps directly to the Oracle AI Database topic "Using Oracle Database Actions and Data Studio Tools." Oracle Docs
NEW QUESTION # 17
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