Oracle AI Cloud Database Services 2025 Professional Practice Exam: Test Your Knowledge 2025

An enterprise is evaluating Oracle Cloud Database Services for their mission-critical applications. They need a solution that provides automated patching, backup, and disaster recovery with minimal administrative overhead. Which service architecture best meets these requirements?

A data science team wants to build and deploy machine learning models directly within their Oracle Autonomous Database without moving data to external platforms. Which feature should they leverage?

Your organization needs to provision an Oracle Autonomous Database for development purposes. Which provisioning option provides the most cost-effective solution while maintaining the ability to scale up for testing periods?

A database administrator notices unusual query patterns that might indicate a security breach. Which Oracle Cloud Database security feature should be used to identify and analyze potentially malicious database activities?

An organization wants to understand the underlying infrastructure differences between Autonomous Database Serverless and Autonomous Database on Dedicated Exadata Infrastructure. What is the PRIMARY architectural distinction?

A data scientist needs to perform feature engineering on large datasets stored in Autonomous Database before training ML models. Which OML capability would be MOST efficient for this task?

Your company is implementing a hybrid cloud strategy and needs to provision Oracle databases both on-premises and in Oracle Cloud Infrastructure with consistent management interfaces. Which service should you recommend?

A machine learning pipeline requires automated retraining of models when new data arrives in database tables. Which Oracle ML feature combination would best support this requirement?

An application team needs to provision a test database that is an exact clone of their production Autonomous Database, including all data, for testing a major application upgrade. What is the FASTEST method to accomplish this?

Your organization needs to implement comprehensive security monitoring for sensitive data in Autonomous Database. Which Oracle Data Safe features should be configured FIRST to establish a security baseline?

A development team is experiencing performance degradation in their Autonomous Database during peak hours. Which feature should they enable to automatically handle workload increases without manual intervention?

An organization wants to implement predictive maintenance using machine learning on sensor data stored in their Autonomous Database. The model needs to score new data in real-time as it arrives. What is the recommended architecture?

A company needs to implement database encryption for data at rest and in transit in their Oracle Cloud Database Service while maintaining the ability to search encrypted data efficiently. Which combination of Oracle security features should be implemented?

Your team is building a recommendation engine and needs to implement collaborative filtering using machine learning algorithms that can handle sparse matrices efficiently. Which OML algorithm category is most appropriate?

A database administrator needs to migrate an on-premises Oracle Database to Autonomous Database with minimal downtime. The database is 5TB with continuous transaction activity. What is the recommended migration approach?

An enterprise is designing a multi-region disaster recovery architecture for their Autonomous Database that requires RPO of near-zero and RTO under 2 minutes. They need automatic failover capabilities. Which Oracle Cloud Database feature combination meets these requirements?

A data science team is implementing an AutoML solution using OML AutoML for classification tasks. After running AutoML, they receive multiple models with different algorithms and hyperparameters. The top model uses a neural network with 95% accuracy, and the second model uses SVM with 94% accuracy but 10x faster inference time. What factor should primarily guide model selection for a real-time fraud detection system processing thousands of transactions per second?

Your organization operates a globally distributed application using Autonomous Database with users in North America, Europe, and Asia. Users in Asia report slow query performance for read operations. The application performs 80% reads and 20% writes. What architectural enhancement would BEST address this performance issue while maintaining data consistency for writes?

A security audit reveals that your Autonomous Database contains sensitive customer information that must be protected according to GDPR requirements. The production application needs access to real data, but non-production environments should not contain actual sensitive data. Which combination of Oracle Data Safe features provides comprehensive protection while maintaining development productivity?

An ML engineering team needs to deploy multiple versions of machine learning models simultaneously to perform A/B testing, with the ability to route 80% of traffic to the stable model and 20% to the new model while collecting performance metrics. Using OML Services, what is the most effective implementation approach?