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Duration 35 hours (5 days)
Course Outline
Introduction to ODI and Architecture
- ODI fundamentals: The ELT approach and how it differs from traditional ETL
- Key elements: Repositories, Agents, Topology, and Security
- Overview of installation and environment setup
ODI Studio and Development Tools
- Exploring ODI Studio: Designer, Topology, Operator, and Security sections
- Managing Projects, Models, and Datastores
- Utilizing reverse-engineered metadata
Designing Mappings and Interfaces
- Building mappings with the graphical interface and ODI components
- Applying procedures, variables, and packages within mappings
- Strategies for error management and data validation
Knowledge Modules and ELT Execution
- Understanding Knowledge Modules (KMs) and their classifications
- Choosing and customizing KMs for various targets
- Performance factors and push-down optimization
Topology, Security, and Connectivity
- Setting up physical and logical schemas and data servers
- Agent types, configuration, and basic high availability
- Security implementation: users, profiles, and repository protection
Scheduling, Deployment, and Operational Management
- Packaging and releasing scenarios
- Scheduling approaches and integration with external schedulers
- Monitoring jobs and troubleshooting via Operator and Logs
Advanced Techniques and Integration Patterns
- CDC patterns, incremental loading, and change data capture methods
- Integration with Big Data sources and Hadoop ecosystems
- Best practices for modular and maintainable integration projects
Hands-on Labs and Real-World Case Study
- End-to-end lab: Designing, building, and deploying an ODI scenario
- Performance tuning lab: Analyzing and optimizing a slow mapping
- Case study analysis: Architectural decisions and key takeaways
Summary and Next Steps
- Recap of core ODI concepts and integration design principles
- Discussion on production deployment strategies and optimization methods
- Exploring further learning paths and certification opportunities
Requirements
- A solid grasp of relational database concepts
- Proficiency in SQL
- Knowledge of ETL or data integration principles
Target Audience
- ETL and Data Integration Developers
- Data Architects and Engineers
- DBA and Middleware Engineers involved in integration solutions
Testimonials (1)
good explanation on each points and provide assignment for practices.
