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Course Outline

Introduction to ODI Fundamentals and Architecture

  • Core ODI concepts: The ELT methodology and its distinctions from traditional ETL
  • Key architectural elements: Repositories, Agents, Topology, and Security frameworks
  • Overview of installation procedures and environment configuration

ODI Studio Interface and Development Tools

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

Designing Data Mappings and Interfaces

  • Building mappings using the graphical interface and native ODI components
  • Integrating procedures, variables, and packages within mapping workflows
  • Strategies for error handling and ensuring data validity

Knowledge Modules and ELT Execution Strategies

  • Exploring Knowledge Modules (KMs) and their various categories
  • Selecting and customizing KMs for diverse target platforms
  • Performance optimization techniques, including push-down logic

Topology, Security, and Connectivity Configuration

  • Setting up physical and logical schemas, along with data servers
  • Configuring Agent types, settings, and foundational high-availability setups
  • Establishing security protocols: user management, profiles, and repository safeguards

Scheduling, Deployment, and Operational Oversight

  • Package creation and scenario deployment procedures
  • Scheduling methodologies and integration with external scheduler systems
  • Job monitoring and issue resolution using Operator and Log tools

Advanced Techniques and Integration Patterns

  • Implementing CDC patterns, incremental loads, and change data capture strategies
  • Connecting with Big Data sources and Hadoop-based ecosystems
  • Best practices for creating modular, sustainable integration projects

Practical Labs and Real-World Case Studies

  • Comprehensive lab: Designing, building, and deploying a complete ODI scenario
  • Performance lab: Diagnosing and optimizing inefficient mappings
  • Case study analysis: Examining architectural choices and key takeaways

Course Summary and Future Directions

  • Recap of essential ODI concepts and integration design best practices
  • Discussion on production deployment strategies and advanced optimization methods
  • Identifying further learning pathways and professional certification options

Requirements

  • A solid grasp of relational database principles
  • Practical proficiency in SQL
  • Familiarity with ETL methodologies or broader data integration concepts

Target Audience

  • ETL and Data Integration Developers
  • Data Architects and Engineers
  • DBAs and Middleware Engineers tasked with integration solutions
 35 Hours

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