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Course Outline

Introduction to ODI and Architecture

  • ODI concepts: ELT approach and differences from traditional ETL.
  • Core components: Repositories, Agents, Topology, and Security.
  • Installation overview 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.
  • Utilizing procedures, variables, and packages within mappings.
  • Implementing error handling and data validation strategies.

Knowledge Modules and ELT Execution

  • Understanding Knowledge Modules (KMs) and their categories.
  • Selecting and customizing KMs for various target systems.
  • Performance considerations and push-down optimization techniques.

Topology, Security, and Connectivity

  • Configuring physical and logical schemas along with data servers.
  • Understanding agent types, configuration, and basics of high availability.
  • Security setup: managing 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 the 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 creating modular and 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: reviewing architecture decisions and key 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 data integration concepts.

Audience

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

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