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Oracle 1z0-1195-26 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| 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% | - 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 |
| Building Low-Code Applications and Agentic AI | 10% | - Describe Oracle APEX as Oracle's low-code platform - Choose the appropriate Agent Factory capability for a no-code AI agent use case |
| Implementing Select AI and AI Vector Search in Autonomous AI Database | 20% | - Determine how AI Vector Search supports GenAI pipelines and RAG - Describe Select AI in Autonomous AI Database - Apply AI Vector Search to combined semantic and business-data search scenarios |
| Working with JSON and Graph in Oracle AI Database | 20% | - 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 |
| Using Oracle Database Actions and Data Studio Tools | 15% | - Describe Database Actions and core development tools - Apply Data Studio capabilities to data discovery, integration, analysis, and sharing tasks |
Oracle AI Database Foundations Associate Sample Questions:
Which graph analytics capability is commonly used to rank important vertices based on their relationships?
- A. Vector distance metric
- B. Private endpoint access
- C. JSON Duality View
- D. PageRank
Correct Answer: D 🗳️
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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?
- A. Start with a pre-built agent or template, then use Agent Builder if more customization is needed
- B. Create a prompt-only prototype and publish it without using Agent Factory agent options
- C. Build a custom agent from a blank setup before reviewing any available templates
- D. Configure data-source connections before selecting a template or agent starting point
Correct Answer: A 🗳️
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When comparing a query vector with stored vectors, what does a smaller vector distance indicate?
- A. The stored vectors were created with different models
- B. The query must switch from SQL to GraphQL
- C. The items are more semantically similar
- D. The items require a larger maintenance window
Correct Answer: C 🗳️
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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?
- A. They can reduce administration because every platform shares one security model
- B. They can avoid all data transformation and synchronization work
- C. They can query all data types together with one built-in model automatically
- D. They can create data silos that make integrated access and management harder
Correct Answer: D 🗳️
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A development team needs an Autonomous AI Database deployment that starts small, minimizes setup effort, and can scale easily. Which deployment choice fits this requirement?
- A. Dedicated, because it allows full control over infrastructure configuration and capacity planning
- B. Dedicated, because it requires capacity to be provisioned and scaled by administrators
- C. A fixed-capacity deployment option, because it maintains consistent performance without scaling
- D. Serverless, because it is designed for simple deployment and elastic scaling
Correct Answer: D 🗳️
Explanation: Only visible for Fast2test members. You can sign-up / login (it's free).
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