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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% | - Describe Select AI in Autonomous AI Database - Determine how AI Vector Search supports GenAI pipelines and RAG - Apply AI Vector Search to combined semantic and business-data search scenarios |
| Topic 2: Working with AI and Vector Foundations | 15% | - 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 3: Working with JSON and Graph in Oracle AI Database | 20% | - Explain JSON and Oracle AI Database JSON capabilities - Distinguish when graph capabilities and Property Graph Views fit a business use case - Describe core graph concepts and graph analytic capabilities |
| Topic 4: 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 5: 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 6: 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 |
Oracle AI Database Foundations Associate Sample Questions:
A business wants one data platform where semantic similarity, relational consistency, and SQL-based filtering all work together.
Which statement aligns with this design goal?
- A. Semantic search is usually handled after relational filters are removed from the query flow.
- B. A converged database can keep data consistent while combining vector search with SQL.
- C. SQL filtering is handled in a separate application step after vector search returns results.
- D. Vector search requires data to be modeled as graph paths before SQL predicates are applied.
Which JSON feature helps represent repeating child data inside one document?
- A. A flat property list with each child stored as a separate document
- B. A scalar property that stores one child value
- C. Arrays and nested objects
- D. A document identifier that points to an external table only
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How can developers create vectors for data objects in Oracle AI Database 26ai?
- A. By defining every vector as a JSON document manually
- B. By using a built-in vectorization function
- C. By loading the data into a separate vector service before querying it
- D. By converting all source objects into Property Graph Views first
Explanation: Only visible for Prep4SureReview members. You can sign-up / login (it's free).
Which graph analytics capability is commonly used to rank important vertices based on their relationships?
- A. JSON Duality View
- B. Private endpoint access
- C. PageRank
- D. Vector distance metric
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Which example is a common AI use case?
- A. Listing database tables alphabetically in a schema browser
- B. Detecting fraudulent transactions from behavior patterns
- C. Rotating an encryption key on a fixed compliance schedule
- D. Manually assigning a subnet CIDR during database provisioning
Explanation: Only visible for Prep4SureReview members. You can sign-up / login (it's free).
