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Oracle 1z0-1195-26 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Implementing Select AI and AI Vector Search in Autonomous AI Database | 20% | - 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 |
| Topic 2: 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 |
| Topic 3: Using Oracle Database Actions and Data Studio Tools | 15% | - Apply Data Studio capabilities to data discovery, integration, analysis, and sharing tasks - Describe Database Actions and core development tools |
| Topic 4: 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 |
| Topic 5: Identifying Oracle AI Database 26ai Strategy and Autonomous AI Database Basics | 20% | - Create an Autonomous AI Database Serverless instance for a basic workload - Describe Autonomous AI Database characteristics, offerings, and deployment choices - Explain modern data characteristics and the Oracle AI Database 26ai converged strategy |
| Topic 6: Working with AI and Vector Foundations | 15% | - Describe AI, AGI, and machine learning foundations - Apply vector distance and indexing concepts to similarity search needs - Explain vectors, embeddings, and the Oracle VECTOR data type |
Oracle AI Database Foundations Associate Sample Questions:
A manufacturer needs graph analysis that reflects inserts and updates from operational tables immediately.
How does a Property Graph View support this requirement?
- A. It provides graph visualization while requiring a separate platform for graph query execution
- B. It converts source tables into JSON collections before graph queries can run
- C. It uses metadata definitions so graph queries read current data from referenced objects
- D. It stores a separate graph copy that is refreshed only during scheduled batch jobs
Correct Answer: C 🗳️
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A data engineer is creating a vector similarity query and wants to choose the distance metric correctly.
Which guidance should be applied?
- A. Choose the metric based on whether the data also has JSON attributes.
- B. Choose the metric based on the database maintenance schedule.
- C. Choose the metric based on the number of rows in the table.
- D. Choose the distance metric based on the embedding model that produced the vectors.
Correct Answer: D 🗳️
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Why do developers often use JSON in applications?
- A. It maps well to application objects and supports nested structures.
- B. It can store only numeric values and arrays.
- C. It requires a fixed schema before any data can be stored.
- D. It replaces the need for APIs and CRUD operations.
Correct Answer: A 🗳️
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Which set is included in the Oracle AI Database 26ai converged approach?
- A. Relational, JSON, vector, graph, and spatial
- B. JSON, document APIs, storage buckets, monitoring, and billing
- C. Relational, XML, spatial, external-only graph stores, and separate vector databases
- D. Relational, JSON, vector, object-only files, and separate document stores
Correct Answer: A 🗳️
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A team needs faster similarity search at scale and accepts approximate top-K results. Which feature should they use?
- A. A graph view with ONE ROW PER STEP
- B. A vector index with approximate search
- C. A standard B-tree index optimized for exact match and range queries
- D. A JSON duality view with update restrictions
Correct Answer: B 🗳️
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