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Course Outline
Introduction to ODI and its Architectural Framework
- ODI fundamentals: The ELT methodology and its distinctions from conventional ETL
- Key components: Repositories, Agents, Topology, and Security mechanisms
- Overview of installation procedures and environment structure
ODI Studio and Development Tools
- Exploring ODI Studio: The Designer, Topology, Operator, and Security panels
- Managing Projects, Models, and Datastores
- Utilizing reverse-engineered metadata effectively
Creating Mappings and Interfaces
- Building mappings using the graphical interface and native ODI components
- Incorporating procedures, variables, and packages into mapping logic
- Implementing error handling and data validation strategies
Knowledge Modules and ELT Execution
- Comprehending Knowledge Modules (KMs) and their respective categories
- Choosing and tailoring KMs for various target platforms
- Addressing performance factors and push-down optimization techniques
Topology, Security, and Connectivity
- Setting up physical and logical schemas along with data servers
- Agent types, configuration specifics, and basic high availability concepts
- Establishing security: user management, profiles, and repository safeguards
Scheduling, Deployment, and Operational Oversight
- Packaging scenarios and executing deployments
- Scheduling approaches and integration with external scheduler tools
- Job monitoring and troubleshooting via Operator and Log files
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 building modular and maintainable integration projects
Practical Labs and Real-World Case Studies
- End-to-end exercise: Designing, implementing, and deploying an ODI scenario
- Performance tuning session: Analyzing and optimizing sluggish mappings
- Case study review: Architectural decision-making and key takeaways
Conclusion and Future Steps
- Recap of essential ODI concepts and integration design principles
- Discussion on production deployment strategies and optimization methods
- Exploration of further learning paths and certification opportunities
Requirements
- A solid grasp of relational database principles
- Proficiency in SQL
- Knowledge of ETL or general data integration concepts
Target Audience
- ETL and data integration developers
- Data architects and engineers
- DBAs and middleware engineers overseeing integration solutions
35 Hours
Testimonials (1)
good explanation on each points and provide assignment for practices.
