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Course Outline

Introduction to ODI and Architecture

  • ODI concepts: The ELT approach and distinctions from traditional ETL
  • Core 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
  • Projects, Models, and Datastores
  • Working with reverse-engineered metadata

Designing Mappings and Interfaces

  • Creating mappings using the graphical interface 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 respective categories
  • Selecting and customizing KMs for various targets
  • Performance considerations and push-down optimization techniques

Topology, Security, and Connectivity

  • Configuring physical and logical schemas as well as data servers
  • Agent types, configuration, and basics of high availability
  • 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 developing modular, maintainable 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 a slow mapping
  • Case study walkthrough: exploring architecture decisions and lessons learned

Summary and Next Steps

  • Reviewing key ODI concepts and integration design principles
  • Discussing production deployment strategies and optimization techniques
  • Exploring further learning paths and certification options

Requirements

  • A solid understanding of relational database concepts
  • Practical experience with SQL
  • Familiarity with ETL or general data integration concepts

Target Audience

  • ETL and data integration developers
  • Data architects and engineers
  • DBAs and middleware engineers responsible for integration solutions
 35 Hours

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