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Course Outline
Enterprise Architecture and Pipeline Design
- Structuring multi-layer ETL architectures.
- Crafting modular, reusable components.
- Implementing hybrid approaches across various systems.
Advanced Performance Engineering
- Optimizing performance at the step level.
- Strategies for managing parallelism and threading.
- Monitoring pipelines under high load conditions.
Automation, Scripting, and Custom Extensions
- Incorporating scripting directly within transformations.
- Building custom plugins to extend functionality.
- Expanding PDI capabilities using Java and JavaScript.
Complex Data Processing and Integrations
- Managing real-time and streaming data integrations.
- Interacting with big data platforms.
- Advanced techniques for file and API processing.
Data Governance, Security, and Compliance
- Securing transformations and managing credentials.
- Establishing data lineage and traceability.
- Addressing regulatory and compliance requirements.
Enterprise Orchestration and Scheduling
- Managing extensive job networks.
- Designing for error recovery and failover.
- Coordinating environment-level orchestration.
Repository, Version Control, and CI/CD
- Developing enterprise repository strategies.
- Integrating PDI workflows with Git.
- Implementing continuous deployment patterns.
Deployment, Monitoring, and Production Operations
- Facilitating solution promotion across environments.
- Leveraging operational tooling and dashboards.
- Achieving end-to-end production readiness.
Conclusion and Future Directions
Requirements
- A foundational understanding 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 responsible for managing complex data integration workloads.
21 Hours
Testimonials (1)
It's a hands-on session.
