This course provides foundational knowledge and practical skills for administering Oracle AI Database. It covers database architecture, installation and configuration, multitenant administration, storage management, security, backup and recovery, performance monitoring, and routine maintenance.

The course also introduces the administration requirements of AI Vector Search, including vector storage, indexing, and resource considerations. The scope aligns with Oracle AI Database 26ai and its multitenant and AI capabilities.

 

Duration 5 Day – 35 hrs.

 

Objectives

• Explain Oracle AI Database architecture and core administrative responsibilities.
• Install, configure, and create an Oracle database environment.
• Manage database instances, network connectivity, and database services.
• Administer container databases and pluggable databases.
• Manage tablespaces, datafiles, schema objects, and storage utilization.
• Configure users, roles, privileges, profiles, and auditing.
• Perform database backup and recovery using Recovery Manager.
• Transfer data using Oracle Data Pump.
• Monitor database health and investigate common performance issues.
• Explain administrative considerations for AI Vector Search workloads.
• Establish routine maintenance, patching, and availability procedures.

 

Target Audience 

• Junior and aspiring Oracle database administrators.
• Database support engineers and application support specialists.
• System administrators responsible for Oracle database environments.
• IT operations professionals supporting enterprise databases.
• Developers transitioning into database administration.
• Technical professionals supporting AI applications that use Oracle databases.

 

Prerequisites 

• Basic knowledge of relational databases, tables, keys, and relationships.
• Familiarity with SQL, including queries and basic data definition and manipulation states.
• Basic Linux command-line skills and familiarity with files, permissions, and processes.
• Basic understanding of networking, including IP addresses, hostnames, and ports.
• Prior exposure to Oracle Database is helpful but not required.

Course Outline 

Day 1: Database Foundations and Environment Setup

Module 1: Introduction to Oracle AI Database

• Oracle AI Database capabilities and common use cases.
• Database administrator roles and responsibilities.
• Deployment options and edition considerations.
• Overview of AI features from an administration perspective.

 Module 2: Oracle Database Architecture

• Database instances and physical database structures.
• Memory structures and background processes.
• Datafiles, control files, and online redo logs.
• Container database and pluggable database architecture.
• Data dictionary and dynamic performance views.

 Module 3: Installation and Initial Configuration

• Operating system and installation prerequisites.
• Oracle software installation and environment settings.
• Database creation using Database Configuration Assistant.
• Administrative connections using SQL tools.
• Listener configuration and client connectivity.
• Database startup, shutdown, and initialization parameters.

 

Day 2: Multitenant, Storage, and Schema Administration

Module 4: Managing Container and Pluggable Databases

• Connecting to containers and managing container context.
• Creating and configuring pluggable databases.
• Opening, closing, and saving pluggable database state.
• Cloning, unplugging, and plugging pluggable databases.
• Managing database services for application connections.

 Module 5: Managing Database Storage

• Logical and physical storage structures.
• Creating and managing tablespaces and datafiles.
• Temporary and undo tablespaces.
• Space allocation, automatic extension, and capacity monitoring.
• Redo log and control file management fundamentals.

 Module 6: Managing Schema Objects and Data Movement

• Administration of tables, indexes, and constraints.
• Object ownership and storage quotas.
• Managing invalid objects and dependencies.
• Exporting and importing data using Oracle Data Pump.
• Common data movement issues and troubleshooting.

  

Day 3: Security, Backup, and Recovery

Module 7: Database Security Administration

• Creating and managing common and local users.
• Assigning system privileges, object privileges, and roles.
• Applying least privilege and separation of duties.
• Configuring profiles and password policies.
• Unified auditing fundamentals.
• Encryption and secure connection concepts.

Module 8: Backup Configuration and Management

• Backup requirements and recovery objectives.
• Recovery Manager architecture and connections.
• ARCHIVELOG mode and the fast recovery area.
• Full and incremental database backups.
• Control file and server parameter file backups.
• Backup retention, validation, and maintenance.

 Module 9: Database Recovery Fundamentals

• Identifying instance, media, and user error scenarios.
• Restoring and recovering databases and datafiles.
• Complete and point-in-time recovery concepts.
• Pluggable database backup and recovery considerations.
• Flashback capabilities and their prerequisites.
• Verifying database availability after recovery.

  

Day 4: Monitoring, Performance, and AI Workloads

Module 10: Database Health Monitoring and Troubleshooting

• Reviewing alert logs and diagnostic files.
• Monitoring sessions, transactions, and resource usage.
• Identifying blocking sessions and lock contention.
• Investigating connectivity and space-related errors.
• Establishing operational baselines and alerts.

 Module 11: Performance Management Fundamentals

• CPU, memory, storage, and input/output considerations.
• Wait events and common performance bottlenecks.
• Optimizer statistics and execution plan fundamentals.
• Identifying resource-intensive SQL.
• Introduction to workload repositories and diagnostic tools.
• Licensing considerations for optional management packs.

 Module 12: Administering AI Vector Search Workloads 

• Vector data, embeddings, and similarity search concepts.
• Storing vectors alongside relational data.
• Overview of vector indexes and their management.
• Memory and storage planning for vector workloads.
• Access control and external model connection considerations.
• Monitoring vector workload performance and growth.

  

Day 5: Maintenance, Availability, and Operational Management

Module 13: Routine Database Maintenance and Automation

• Establishing daily, weekly, and monthly maintenance tasks.
• Scheduling administrative jobs with Oracle Scheduler.
• Managing diagnostic files, audit data, and storage growth.
• Monitoring scheduled jobs and backup outcomes.
• Maintaining operational records and configuration documentation.

 Module 14: Patching, Upgrades, and Change Management

• Understanding release updates and patch planning.
• Preparing pre-change checks and recovery arrangements.
• Overview of patching tools and workflows.
• Upgrade planning and compatibility considerations.
• Post-change validation and rollback planning.

 Module 15: High Availability and Operational Readiness

• Availability requirements and common failure scenarios.
• Introduction to Oracle Data Guard and standby databases.
• Introduction to Oracle Real Application Clusters.
• Backup strategy versus high availability planning.
• Incident handling and escalation procedures.
• Developing database administration runbooks and handover documentation.