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Last Updated: Sep 13, 2026
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Oracle 1z0-1195-26 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| 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 |
| 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 |
| Identifying Oracle AI Database 26ai Strategy and Autonomous AI Database Basics | 20% | - Describe Autonomous AI Database characteristics, offerings, and deployment choices - Create an Autonomous AI Database Serverless instance for a basic workload - Explain modern data characteristics and the Oracle AI Database 26ai converged strategy |
| 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 JSON and Graph in Oracle AI Database | 20% | - Describe core graph concepts and graph analytic capabilities - Explain JSON and Oracle AI Database JSON capabilities - Distinguish when graph capabilities and Property Graph Views fit a business use case |
| Working with AI and Vector Foundations | 15% | - Apply vector distance and indexing concepts to similarity search needs - Describe AI, AGI, and machine learning foundations - Explain vectors, embeddings, and the Oracle VECTOR data type |
Oracle AI Database Foundations Associate Sample Questions:
Which pair correctly matches an AI domain to an example?
- A. Vision - image classification
- B. Speech - product demand prediction
- C. Forecasting - entity extraction from text
- D. Language - object detection in photos
Correct Answer: A 🗳️
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What is the operational benefit of using a converged database instead of several point-solution databases?
- A. It can reduce operational complexity by using a more consistent security and patching approach
- B. It guarantees that all workloads use the same physical schema and access method
- C. It automatically removes the need to review security policies for database workloads
- D. It requires every application team to maintain a separate synchronization process
Correct Answer: A 🗳️
Explanation: Only visible for Exam4Labs members. You can sign-up / login (it's free).
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?
- A. Replace all policy documents with graph edge IDs.
- B. Retrieve semantically similar document chunks to provide context for generation.
- C. Use only keyword matching because enterprise data must not use embeddings.
- D. Return unfiltered database patches as the answer context.
Correct Answer: B 🗳️
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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. Configure data-source connections before selecting a template or agent starting point
- D. Build a custom agent from a blank setup before reviewing any available templates
Correct Answer: A 🗳️
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A recruiting application must find the top job postings that semantically match a candidate's resume, but only in the candidate's city. How should the application meet this requirement?
- A. Use one SQL query that combines relational filters with vector distance ordering
- B. Export all job postings to a separate vector platform and remove city filtering
- C. Replace job descriptions with graph edge labels only
- D. Use Early maintenance so results are ranked sooner
Correct Answer: A 🗳️
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