Oracle AI Database Foundations Associate: 1z0-1195-26 Exam

"Oracle AI Database Foundations Associate", also known as 1z0-1195-26 exam, is a Oracle Certification. With the complete collection of questions and answers, iPassleader has assembled to take you through 54 Q&As to your 1z0-1195-26 Exam preparation. In the 1z0-1195-26 exam resources, you will cover every field and category in Oracle Cloud Infrastructure Certification helping to ready you for your successful Oracle Certification.

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  • Updated on: Sep 09, 2026
  • No. of Questions: 54 Questions & Answers

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  • Updated on: Sep 09, 2026
  • No. of Questions: 54 Questions & Answers

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Oracle 1z0-1195-26 Exam Syllabus Topics:

SectionObjectives
Topic 1: Using Oracle Database Actions and Data Studio Tools- Apply Data Studio capabilities to data discovery, integration, analysis, and sharing tasks
- Describe Database Actions and core development tools
Topic 2: Identifying Oracle AI Database 26ai Strategy and Autonomous AI Database Basics- 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
Topic 3: Working with JSON and Graph in Oracle AI Database- 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
Topic 4: Working with AI and Vector Foundations- Apply vector distance and indexing concepts to similarity search needs
- Explain vectors, embeddings, and the Oracle VECTOR data type
- Describe AI, AGI, and machine learning foundations
Topic 5: Building Low-Code Applications and Agentic AI- Choose the appropriate Agent Factory capability for a no-code AI agent use case
- Describe Oracle APEX as Oracle's low-code platform
Topic 6: Implementing Select AI and AI Vector Search in Autonomous AI Database- Apply AI Vector Search to combined semantic and business-data search scenarios
- Determine how AI Vector Search supports GenAI pipelines and RAG
- Describe Select AI in Autonomous AI Database

Oracle AI Database Foundations Associate Sample Questions:

In a property graph, what are vertices and edges?

  • A. Vertices are storage partitions, and edges are encryption keys
  • B. Vertices are JSON collections, and edges are maintenance policies
  • C. Vertices represent entities, and edges represent relationships between them
  • D. Vertices are path lengths and edges are SQL functions
Answer: C

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Which set of characteristics is commonly used to describe Autonomous AI Database?

  • A. Self-coding, self-licensing, and self-networking
  • B. Self-training, self-upgrading, and self-documenting
  • C. Self-driving, self-securing, and self-repairing
  • D. Self-hosted, self-audited, and self-architected
Answer: C

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What is OSON in Oracle AI Database JSON support?

  • A. An optimized binary format for JSON storage
  • B. A SQL worksheet page in Database Actions
  • C. A maintenance schedule for JSON collections
  • D. A visualization tool for graph queries
Answer: A

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Which sequence matches a simple RAG pipeline?

  • A. Provision an application workspace, then skip retrieval and generate answers directly from schema metadata
  • B. Build a graph model, then schedule maintenance, then create embeddings after generation
  • C. Create embeddings, store vectors, retrieve relevant chunks by similarity, then generate an answer
  • D. Generate an answer first, then create embeddings only if the answer looks weak
Answer: C

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A vector index will not fit entirely in memory. Which index organization option should be considered for use?

  • A. TARGET ACCURACY
  • B. INMEMORY NEIGHBOR GRAPH
  • C. EXACT SEARCH ONLY
  • D. NEIGHBOR PARTITIONS
Answer: D

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