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Course Outline
Introduction to n8n for Data Integration
- Overview of n8n’s data integration capabilities
- Key concepts of ETL in n8n
- Common use cases in data integration and analytics
Connecting to Data Sources
- Setting up database integrations (MySQL, PostgreSQL, etc.)
- Connecting to APIs for data extraction
- Integrating with cloud storage solutions (e.g., Google Drive, Dropbox)
Data Transformation Techniques
- Cleaning and preparing data for analysis
- Using n8n nodes for data manipulation
- Implementing custom logic and transformations in workflows
Automating ETL Workflows
- Building ETL workflows to automate data flows
- Scheduling workflows for regular data updates
- Setting up conditional workflows for dynamic data handling
Integrating with Analytics and Reporting Tools
- Exporting data to analytics platforms (e.g., Google Analytics, Power BI)
- Setting up automated reports and notifications
- Using webhooks for real-time data processing
Monitoring and Troubleshooting Data Workflows
- Tracking data flow and job status in n8n
- Handling errors and data inconsistencies
- Debugging workflows for optimized performance
Best Practices in Data Integration
- Data security and privacy considerations
- Ensuring data quality and consistency
- Optimizing workflows for scalability
Scaling Data Integration Efforts
- Deploying workflows across multiple environments
- Managing and updating workflows for new data needs
- Preparing for future developments in data integration
Summary and Next Steps
Requirements
- Basic knowledge of ETL processes
- Experience with data integration or manipulation tools
- Familiarity with APIs and database systems
Audience
- Data analysts
- Integration specialists
21 Hours
