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Course Outline

Introduction to ODI and Architecture

  • Core ODI concepts: The ELT approach and its distinctions from traditional ETL
  • Essential components: Repositories, Agents, Topology, and Security frameworks
  • Installation insights and environment configuration overview

ODI Studio and Development Components

  • Navigating ODI Studio: Utilizing the Designer, Topology, Operator, and Security panels
  • Managing Projects, Models, and Datastores
  • Working with reverse-engineered metadata

Designing Mappings and Interfaces

  • Building mappings via 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 various categories
  • Selecting and customizing KMs for specific target systems
  • Performance considerations and push-down optimization techniques

Topology, Security, and Connectivity

  • Configuring physical and logical schemas along with data servers
  • Agent types, configuration settings, and high availability fundamentals
  • Security setup: User management, profiles, and repository protection

Scheduling, Deployment, and Operational Management

  • Package and scenario deployment processes
  • Scheduling strategies and integration with external schedulers
  • Job monitoring and troubleshooting using Operator and Logs

Advanced Techniques and Integration Patterns

  • CDC patterns, incremental loading, and change data capture methodologies
  • Integration with Big Data sources and Hadoop ecosystems
  • Best practices for creating 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 slow mappings
  • Case study review: Exploring architecture decisions and key takeaways

Summary and Next Steps

  • Review of critical ODI concepts and integration design principles
  • Discussion on production deployment strategies and optimization methods
  • Exploring further learning paths and certification options

Requirements

  • A solid grasp of relational database principles
  • 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 overseeing integration solutions
 35 Hours

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