Updated: Sep 08, 2026
No. of Questions: 54 Questions & Answers with Testing Engine
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| Certification Vendor: | Oracle |
|---|---|
| Exam Name: | Oracle AI Database Foundations Associate |
| Exam Number: | 1Z0-1195-26 |
| Certificate Validity Period: | 10 years |
| Exam Duration: | 60 minutes |
| Available Languages: | English, Japanese |
| Passing Score: | 65% |
| Exam Format: | Online Proctored, Multiple Choice |
| Related Certifications: | Oracle AI Database Certified Foundations Associate Oracle Data Platform 2025 Certified Foundations Associate |
| Exam Price: | Free |
| Real Exam Qty: | 40 |
| Sample Questions: | Oracle 1z0-1195-26 Sample Questions |
| Exam Way: | Online proctored exam; Japanese delivery is also available. |
| Pre Condition: | No prerequisite exam or prior certification is required. |
| Official Syllabus URL: | https://www.oracle.com/education/certification/ |
| Section | Objectives |
|---|---|
| Topic 1: 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 |
| Topic 2: Working with AI and Vector Foundations | - 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 |
| Topic 3: Using Oracle Database Actions and Data Studio Tools | - Describe Database Actions and core development tools - Apply Data Studio capabilities to data discovery, integration, analysis, and sharing tasks |
| Topic 4: Working with JSON and Graph in Oracle AI Database | - Describe core graph concepts and graph analytic capabilities - Distinguish when graph capabilities and Property Graph Views fit a business use case - Explain JSON and Oracle AI Database JSON capabilities |
| Topic 5: Building Low-Code Applications and Agentic AI | - 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 | - Create an Autonomous AI Database Serverless instance for a basic workload - Explain modern data characteristics and the Oracle AI Database 26ai converged strategy - Describe Autonomous AI Database characteristics, offerings, and deployment choices |
Question 1
Which set of characteristics is commonly used to describe Autonomous AI Database?
A. Self-driving, self-securing, and self-repairing
B. Self-training, self-upgrading, and self-documenting
C. Self-coding, self-licensing, and self-networking
D. Self-hosted, self-audited, and self-architected
Question 2
When comparing a query vector with stored vectors, what does a smaller vector distance indicate?
A. The query must switch from SQL to GraphQL
B. The stored vectors were created with different models
C. The items are more semantically similar
D. The items require a larger maintenance window
Question 3
Which statement describes Artificial Intelligence?
A. Systems replace databases by storing all data as graphs
B. Systems are identical to AGI in all current enterprise products
C. Systems use data and algorithms to perform tasks that normally require human intelligence
D. Systems eliminate the need for training data in every use case
Question 4
A retailer wants to find products semantically similar to a shopper's description, but only from items that are in stock and sold in the shopper's region. Which design meets this requirement?
A. Use a single SQL statement that combines stock and region filters with vector ranking
B. Use a property graph because vector search cannot work with business predicates
C. Use JSON Duality Views because similarity search requires document-only access
D. Use vector search only, then manually remove unavailable products outside the database
Question 5
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 distance metric based on the embedding model that produced the vectors.
B. Choose the metric based on the number of rows in the table.
C. Choose the metric based on whether the data also has JSON attributes.
D. Choose the metric based on the database maintenance schedule.
Solutions:
| Question 1 Answer: A | Question 2 Answer: C | Question 3 Answer: C | Question 4 Answer: A | Question 5 Answer: A |
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