Eğitim İçeriği
Introduction to ODI and Architecture
- ODI concepts: ELT approach, differences from traditional ETL
- Core components: Repositories, Agents, Topology, and Security
- Installation overview and environment layout
ODI Studio and Development Components
- Navigating ODI Studio: Designer, Topology, Operator, and Security panels
- Projects, Models, and Datastores
- Working with reverse-engineered metadata
Designing Mappings and Interfaces
- Creating mappings with graphical interface and ODI components
- Using procedures, variables, and packages in mappings
- Error handling and data validation strategies
Knowledge Modules and ELT Execution
- Understanding Knowledge Modules (KMs) and their categories
- Selecting and customizing KMs for different targets
- Performance considerations and push-down optimization
Topology, Security, and Connectivity
- Configuring physical and logical schemas and data servers
- Agent types, configuration, and high availability basics
- Security setup: users, profiles, and repository protection
Scheduling, Deployment, and Operational Management
- Packaging and deploying scenarios
- Scheduling strategies and integrating with external schedulers
- Monitoring jobs and troubleshooting with Operator and Logs
Advanced Techniques and Integration Patterns
- CDC patterns, incremental loading, and change data capture approaches
- Integrating with Big Data sources and Hadoop ecosystems
- Best practices for modular, maintainable integration projects
Hands-on Labs and Real-World Case Study
- End-to-end lab: design, implement, and deploy an ODI scenario
- Performance tuning lab: analyze and optimize a slow mapping
- Case study walkthrough: architecture decisions and lessons learned
Summary and Next Steps
- Review key ODI concepts and integration design principles
- Discuss production deployment strategies and optimization techniques
- Explore further learning paths and certification options
Kurs İçin Gerekli Önbilgiler
- An understanding of relational database concepts
- Experience with SQL
- Familiarity with ETL or data integration concepts
Audience
- ETL/Data integration developers
- Data architects and engineers
- DBA and middleware engineers responsible for integration solutions
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