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Course Outline
Enterprise Architecture and Pipeline Design
- Structuring multi-layer ETL architectures.
- Designing modular and reusable components.
- Implementing hybrid approaches across various systems.
Advanced Performance Engineering
- Optimizing performance at the step level.
- Strategies for parallelism and threading.
- Monitoring pipelines under high load.
Automation, Scripting, and Custom Extensions
- Integrating scripting within transformations.
- Creating custom plugins.
- Enhancing PDI capabilities using Java and JavaScript.
Complex Data Processing and Integrations
- Implementing real-time and streaming integrations.
- Interacting with big data platforms.
- Advanced handling of files and API processing.
Data Governance, Security, and Compliance
- Protecting transformations and managing credentials securely.
- Ensuring data lineage and traceability.
- Addressing regulatory and compliance requirements.
Enterprise Orchestration and Scheduling
- Managing extensive job networks.
- Designing error recovery and failover mechanisms.
- Implementing environment-level orchestration.
Repository, Version Control, and CI/CD
- Defining enterprise repository strategies.
- Integrating PDI with Git.
- Applying continuous deployment patterns.
Deployment, Monitoring, and Production Operations
- Promoting solutions across different environments.
- Utilizing operational tooling and dashboards.
- Achieving end-to-end production readiness.
Summary and Next Steps
Requirements
- Familiarity with ETL pipelines and data modeling concepts.
- Practical experience with intermediate-level PDI transformations.
- Proficiency in SQL and scripting languages.
Target Audience
- Senior data engineers.
- ETL architects.
- Professionals overseeing complex data integration workloads.
21 Hours
Testimonials (1)
It's a hands-on session.
