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Course Outline
Advanced Transformation Building Blocks
- Handling complex data types
- Managing fields, metadata, and dynamic data structures
- Developing reusable transformation patterns
Parameters, Variables, and Job-Oriented Design
- Utilizing runtime variables and understanding scoping
- Parameterizing transformations for flexibility
- Structuring parent-child job relationships
Database Integration and Lookup Strategies
- Implementing advanced lookup steps
- Applying effective caching strategies
- Designing efficient joins
Working with Files, APIs, and External Systems
- Processing JSON and XML data
- Invoking REST and SOAP services
- Managing both streaming and batch loads
Error Handling and Data Quality Techniques
- Capturing and routing errors effectively
- Implementing data validation patterns
- Establishing auditing and logging procedures
Performance Tuning Essentials
- Optimizing the design of individual steps
- Considering memory usage and threading implications
- Identifying and resolving performance bottlenecks
Introduction to Repository-Based Development
- Leveraging the Pentaho repository
- Managing versions of transformations and jobs
- Adopting team collaboration best practices
Deployment and Migration Practices
- Promoting jobs across different environments
- Managing configuration settings
- Applying operational best practices
Summary and Next Steps
Requirements
- A solid grasp of fundamental ETL concepts
- Practical experience with Pentaho Data Integration
- Basic familiarity with data warehousing principles
Target Audience
- ETL developers
- Data engineers
- Technical professionals looking to expand their PDI capabilities
21 Hours
Testimonials (1)
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