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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: MySQL HeatWave and NoSQL Services | ~11% | - Oracle NoSQL Database features and use cases - MySQL HeatWave architecture and analytics |
| Topic 2: Converged Database — Multi-Model and AI Capabilities | ~15% | - Oracle AI Vector Search concepts - Select AI and natural language querying - JSON, Graph, Spatial, and key-value data support |
| Topic 3: Oracle Machine Learning and AI Integration | ~15% | - In-database machine learning algorithms - AI agents and LLM integration - Oracle Data Studio and visualization |
| Topic 4: Data Management and Oracle Data Platform Overview | ~11% | - Oracle Data Strategy and multi-cloud deployment models - Data management concepts and data types - Modern data platform value and architecture |
| Topic 5: Autonomous AI Database and Tools | ~16% | - Core features of Autonomous AI Database - Shared vs dedicated infrastructure - Built-in management and query tools |
| Topic 6: Oracle Database Services — Exadata, DBCS, and Engineered Systems | ~11% | - Exadata architecture and features - Database Cloud Service (DBCS) characteristics |
| Topic 7: Security, Resilience, and Cloud Integration | ~21% | - Database security architectures and data protection - High availability, backup, and disaster recovery - Cloud-native database services and deployment strategies |
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질문 # 15
A team needs faster similarity search at scale and accepts approximate top-K results. Which feature should they use?
정답：B
질문 # 16
How is Oracle APEX described?
정답：B
설명：
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.
질문 # 17
Modern applications often need to work with relational data, JSON documents, graph relationships, and vector embeddings. What challenge does using a different specialized database for each need create?
정답：C
설명：
Using a different point-solution database for each data model can create data silos , increasing integration, synchronization, governance, and operational complexity. The uploaded assessment identifies option D as correct. Oracle AI Database 26ai is explicitly positioned as a converged database platform supporting AI, graph, document, spatial, relational, and other application models within one database architecture.
The problem with separate specialized stores is that an application may need to duplicate relational records into a document database, copy embeddings into a vector database, and maintain relationships in a graph database. These copies must remain synchronized as source data changes. Security controls, backups, monitoring, patching, access policies, and application integrations may also differ across platforms.
Oracle's converged model instead allows different representations and workloads to operate on centrally governed data. Oracle specifically notes that the converged platform provides synergy among multiple data models and enables different types of information to be joined and manipulated together.
Therefore, separate databases do not automatically share security or eliminate transformation. Those are precisely the architectural burdens that convergence is intended to reduce.
Study Guide reference: Identifying Oracle AI Database 26ai Strategy and Autonomous AI Database Basics - converged database strategy and elimination of data silos.
질문 # 18
A company wants a GenAI assistant that answers policy questions by grounding responses in its internal documents.
Which use of AI Vector Search best supports this design?
정답：D
설명：
Comprehensive and Detailed 100 to 150 words of Explanation From Oracle AI Database topics:
Retrieval-Augmented Generation grounds an LLM by retrieving relevant enterprise content before generation.
Oracle Select AI with RAG uses AI Vector Search and semantic similarity to locate the top matching document chunks from a vector store, then supplies those retrieved texts together with the user's question to the LLM. This gives the model current, organization-specific context and reduces hallucination risk. Keyword- only retrieval can miss semantically related passages that use different wording, while graph edge identifiers are not a substitute for document content. Returning unfiltered database patches also does not provide targeted grounding. Therefore, the correct design is to retrieve semantically similar chunks and use them as context for generation. This matches Oracle's documented Select AI RAG workflow and the AI/vector foundations objectives. Oracle Docs
질문 # 19
Which statement describes Artificial Intelligence?
정답：A
설명：
Artificial Intelligence describes computing systems designed to perform functions associated with human intelligence, including learning, reasoning, language understanding, recognition, prediction, and decision support. Oracle characterizes AI as computing systems trained to simulate human intelligence and notes that AI systems can learn from data, solve problems, process diverse inputs, and pursue defined objectives. Oracle also describes AI technologies as systems or machines that mimic human intelligence when performing tasks.
Data and algorithms are central to modern AI implementations. Machine-learning models learn patterns from training data, while generative models can synthesize new outputs based on learned representations and prompts. However, AI does not imply that training or grounding data is unnecessary. Nor is current enterprise AI equivalent to Artificial General Intelligence (AGI); most deployed systems remain specialized around particular tasks and workloads.
AI also does not replace database technology. Oracle AI Database instead integrates AI capabilities with relational, JSON, graph, spatial, vector, and other database models so that intelligent applications can operate directly on governed enterprise data. Oracle AI Database 26ai specifically emphasizes AI capabilities while preserving converged data-management functionality. The uploaded question source marks option A as correct.
Study Guide reference: Identifying Oracle AI Database 26ai Strategy and Autonomous AI Database Basics - AI fundamentals and Oracle's AI-enabled database strategy.
질문 # 20
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