n8n for Data Integration

• Basic knowledge of ETL processes
• Experience with data integration or manipulation tools
• Familiarity with APIs and database systems

Audience

• Data analysts
• Integration specialists

n8n is a versatile automation and integration tool that allows for the consolidation and transformation of data across various platforms. This course focuses on using n8n for data integration and ETL processes to streamline analytics and reporting tasks, enabling efficient data flow across systems.

This instructor-led, live training (online or onsite) is aimed at intermediate-level data professionals who wish to use n8n for integrating data from different sources, transforming it, and automating workflows for reporting and analytics.

By the end of this training, participants will be able to:

• Understand data integration concepts and n8n’s role in supporting ETL processes.
• Connect various data sources, such as databases, cloud storage, and APIs, using n8n.
• Transform and clean data for analytical purposes.
• Automate ETL workflows to support data reporting needs across systems.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

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