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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% | - Describe Oracle APEX as Oracle's low-code platform - Choose the appropriate Agent Factory capability for a no-code AI agent use case |
| 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 |
| Implementing Select AI and AI Vector Search in Autonomous AI Database | 20% | - Apply AI Vector Search to combined semantic and business-data search scenarios - Describe Select AI in Autonomous AI Database - Determine how AI Vector Search supports GenAI pipelines and RAG |
| Identifying Oracle AI Database 26ai Strategy and Autonomous AI Database Basics | 20% | - Explain modern data characteristics and the Oracle AI Database 26ai converged strategy - Create an Autonomous AI Database Serverless instance for a basic workload - Describe Autonomous AI Database characteristics, offerings, and deployment choices |
| 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:
Question 1
What happens after a user asks a business question with Select AI?
A. The platform manages prompt engineering, interacts with an LLM, and produces the answer
B. The database disables SQL and switches to document APIs only
C. The user must manually create embeddings before SQL can be generated
D. The system selects database tables and joins without using any schema metadata
Question 2
What is an embedding in the context of AI Vector Search?
A. A graph edge label stored in a property graph
B. A maintenance schedule attached to a database instance
C. A sequence of numbers that represents semantic content
D. A text-only backup of a JSON collection
Question 3
Which example is a common AI use case?
A. Detecting fraudulent transactions from behavior patterns
B. Listing database tables alphabetically in a schema browser
C. Manually assigning a subnet CIDR during database provisioning
D. Rotating an encryption key on a fixed compliance schedule
Question 4
What is the main difference between Autonomous AI Database Serverless and Dedicated deployment choices?
A. Serverless requires customers to manage isolated Exadata infrastructure, while Dedicated is fully shared by default
B. Serverless is simple and elastic, while Dedicated provides isolated private resources and more customization.
C. Serverless and Dedicated differ only in the SQL tools available to developers
D. Serverless is used only for JSON workloads, while Dedicated is used only for relational workloads
Question 5
Which offering is positioned for JSON-centric workloads and includes Oracle Database API for MongoDB?
A. Oracle APEX Service
B. Autonomous AI Lakehouse
C. Autonomous AI JSON Database
D. Autonomous AI Transaction Processing only
Solutions:
| Question 1 Answer: A | Question 2 Answer: C | Question 3 Answer: A | Question 4 Answer: B | Question 5 Answer: C |
