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Course Outline
Introduction to ODI and Architecture
- Core ODI concepts: ELT methodology and distinctions from traditional ETL
- Key components: Repositories, Agents, Topology, and Security
- Overview of installation procedures and environment layout
ODI Studio and Development Components
- Navigating ODI Studio: Utilizing the Designer, Topology, Operator, and Security interfaces
- Management of Projects, Models, and Datastores
- Working with reverse-engineered metadata
Designing Mappings and Interfaces
- Building mappings via graphical interfaces and ODI components
- Incorporating procedures, variables, and packages into mappings
- Strategies for error handling and data validation
Knowledge Modules and ELT Execution
- Understanding Knowledge Modules (KMs) and their classifications
- Selecting and tailoring KMs for various target systems
- Performance optimization and push-down techniques
Topology, Security, and Connectivity
- Configuring physical and logical schemas along with data servers
- Agent types, configuration settings, and an introduction to high availability
- Security configuration: managing users, profiles, and repository protection
Scheduling, Deployment, and Operational Management
- Packaging and deploying integration scenarios
- Scheduling approaches and integration with external schedulers
- Job monitoring and troubleshooting using the Operator interface and logs
Advanced Techniques and Integration Patterns
- Implementation of CDC patterns, incremental loading, and change data capture methods
- Connecting with Big Data sources and the Hadoop ecosystem
- Best practices for creating modular and maintainable integration projects
Hands-on Labs and Real-World Case Study
- Comprehensive lab: end-to-end design, implementation, and deployment of an ODI scenario
- Performance tuning lab: analyzing and optimizing slow-running mappings
- Case study review: insights into architecture decisions and lessons learned
Summary and Next Steps
- Recap of essential ODI concepts and integration design principles
- Discussion on production deployment strategies and optimization techniques
- Exploration of further learning pathways and certification opportunities
Requirements
- A solid grasp of relational database concepts
- Proficiency in SQL
- Familiarity with ETL methodologies or data integration principles
Audience
- ETL and Data integration developers
- Data architects and engineers
- DBAs and middleware engineers tasked with integration solutions
35 Hours
Testimonials (1)
I found his methods very informative
