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Duration 35 hours (5 days)
Course Outline
Introduction to ODI and Architecture
- Core ODI concepts: the ELT approach and how it differs from traditional ETL
- Key components: Repositories, Agents, Topology, and Security
- Overview of installation and environment layout
ODI Studio and Development Components
- Navigating ODI Studio: Designer, Topology, Operator, and Security panels
- Managing Projects, Models, and Datastores
- Utilizing reverse-engineered metadata
Designing Mappings and Interfaces
- Building mappings using the graphical interface and ODI components
- Incorporating procedures, variables, and packages into mappings
- Implementing error handling and data validation strategies
Knowledge Modules and ELT Execution
- Understanding Knowledge Modules (KMs) and their various categories
- Selecting and customizing KMs for specific target environments
- Addressing performance considerations and push-down optimization
Topology, Security, and Connectivity
- Setting up physical and logical schemas and data servers
- Agent types, configuration, and basic high availability principles
- Security configuration: users, profiles, and repository protection
Scheduling, Deployment, and Operational Management
- Packaging and deploying scenarios
- Developing scheduling strategies and integrating with external schedulers
- Monitoring jobs and troubleshooting using 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 maintaining modular and sustainable integration projects
Hands-on Labs and Real-World Case Study
- End-to-end lab: designing, implementing, and deploying an ODI scenario
- Performance tuning lab: analyzing and optimizing slow mappings
- Case study analysis: architectural decisions and key takeaways
Summary and Next Steps
- Reviewing fundamental ODI concepts and integration design principles
- Discussing production deployment strategies and optimization methods
- Exploring advanced 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
- DBAs and middleware engineers involved in integration solutions
Testimonials (1)
good explanation on each points and provide assignment for practices.
