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Course Outline
Enterprise Architecture and Pipeline Design
- Multi-layered ETL architectural frameworks.
- Creating modular and reusable components.
- Implementing hybrid approaches across different systems.
Advanced Performance Engineering
- Optimization techniques at the step level.
- Strategies for parallelism and threading.
- Monitoring pipelines under high load conditions.
Automation, Scripting, and Custom Extensions
- Integrating scripting directly within transformations.
- Building custom plugins.
- Expanding PDI capabilities using Java and JavaScript.
Complex Data Processing and Integrations
- Real-time and streaming data integrations.
- Interoperability with big data platforms.
- Advanced handling of files and APIs.
Data Governance, Security, and Compliance
- Securing transformations and managing credentials.
- Establishing data lineage and traceability.
- Addressing regulatory and compliance requirements.
Enterprise Orchestration and Scheduling
- Oversight of extensive job networks.
- Designing error recovery and failover mechanisms.
- Orchestration at the environment level.
Repository, Version Control, and CI/CD
- Strategies for enterprise repositories.
- Integration of PDI with Git.
- Patterns for continuous deployment.
Deployment, Monitoring, and Production Operations
- Promoting solutions between different environments.
- Utilizing operational tooling and dashboards.
- Ensuring end-to-end readiness for production.
Summary and Next Steps
Requirements
- A solid grasp of ETL pipelines and data modeling concepts.
- Practical experience with intermediate-level PDI transformations.
- Strong proficiency in SQL and scripting languages.
Target Audience
- Senior data engineers.
- ETL architects.
- Professionals overseeing complex data integration operations.
21 Hours
Testimonials (1)
It's a hands-on session.
