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Duration 35 hours (5 days)
Course Outline
Introduction to ODI and Architecture
- ODI concepts: the ELT approach and key 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 using the graphical interface and ODI components
- Utilizing procedures, variables, and packages within mappings
- Strategies for error handling and data validation
Knowledge Modules and ELT Execution
- Understanding Knowledge Modules (KMs) and their categories
- Selecting and customizing KMs for various 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 fundamentals
- Security setup: users, profiles, and repository protection
Scheduling, Deployment, and Operational Management
- Packaging and deploying scenarios
- Scheduling strategies and integration with external schedulers
- Monitoring jobs and troubleshooting using 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
Requirements
- A solid understanding of relational database concepts
- Proficiency in SQL
- Familiarity with ETL or data integration principles
Target Audience
- ETL and Data Integration Developers
- Data Architects and Engineers
- DBAs and Middleware Engineers responsible for integration solutions
Testimonials (1)
good explanation on each points and provide assignment for practices.
