Oracle AI Database Administration Professional Practice Exam: Test Your Knowledge 2025

You are implementing AI Vector Search in Oracle Database to support a similarity search application for product recommendations. Which data type should you use to store vector embeddings?

A database administrator needs to create a vector index to improve similarity search performance on a table containing 10 million product embeddings. Which index type is specifically designed for vector similarity searches in Oracle Database?

Your organization is deploying an AI-powered chatbot that requires semantic search capabilities. You need to configure the distance metric for vector similarity searches. Which distance metric is most commonly used for normalized embeddings from modern language models?

You are experiencing slow performance with vector similarity searches on a large dataset. After investigation, you find that the HNSW index parameters may not be optimal. Which parameter controls the trade-off between search accuracy and index build time?

A company needs to perform vector similarity searches that return the top 50 most similar items from a collection of 5 million vectors. Which SQL function should be used to find the k-nearest neighbors in Oracle Database?

You need to monitor the effectiveness of your vector index. Which approach provides insights into whether the vector index is being used effectively for similarity searches?

Your application requires storing vectors with varying dimensions across different use cases. What is the recommended approach for managing vectors of different dimensionality in Oracle Database?

A data scientist wants to integrate a machine learning model trained in Python using scikit-learn into the Oracle Database. Which Oracle feature enables running Python code directly within the database?

Your team needs to deploy a trained machine learning model for real-time inference within Oracle Database. The model should be accessible via SQL queries. Which approach best accomplishes this requirement?

A company wants to leverage ONNX format models within Oracle Database for inference. What is the primary advantage of using ONNX format for model deployment?

You need to train an AutoML model directly in Oracle Database for a classification task. Which Oracle Machine Learning component automates feature selection, algorithm selection, and hyperparameter tuning?

A financial services company needs to perform feature engineering on transactional data stored in Oracle Database before training ML models. The data volume is 500 GB. What is the most efficient approach?

Your organization uses Oracle Autonomous Database and needs to implement automated performance tuning for workloads that include AI/ML queries. Which feature automatically optimizes SQL execution plans based on workload patterns?

You are managing an Oracle Database that hosts both traditional OLTP workloads and AI model inference workloads. The AI workloads are causing resource contention. What is the best approach to ensure AI workloads don't impact critical business transactions?

Your AI application generates large volumes of temporary vector data during similarity search operations. You notice performance degradation due to temporary tablespace pressure. What is the recommended solution?

You need to implement a backup strategy for an Oracle Database containing ML models, training data, and vector indexes. The RTO requirement is 2 hours and RPO is 15 minutes. Which backup approach best meets these requirements?

An AI application is experiencing inconsistent query performance for vector similarity searches. After investigation, you discover that statistics on the vector column are stale. What is the appropriate action?

Your organization must comply with data privacy regulations that require masking sensitive personal information in training datasets used for machine learning. Which Oracle feature should you implement?

A healthcare application stores patient data and uses ML models for diagnosis predictions. You need to ensure that only authorized data scientists can access the ML models and their training data. Which security approach provides the most granular control?

Your company needs to audit all access to ML models and vector search operations for compliance purposes. Which Oracle feature should you enable to track and log these activities?