Data Pipeline

Build data pipelines and ETL workflows for data integration, transformation, and analytics automation. Based on n8n's data workflow templates.

Overview

This skill covers:

• Data extraction from multiple sources
• Transformation and cleaning
• Loading to destinations
• Scheduling and monitoring
• Error handling and alerts

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ETL Patterns

Basic ETL Flow

┌─────────────┐    ┌─────────────┐    ┌─────────────┐
│   EXTRACT   │───▶│  TRANSFORM  │───▶│    LOAD     │
│             │    │             │    │             │
│ • APIs      │    │ • Clean     │    │ • Database  │
│ • Databases │    │ • Map       │    │ • Warehouse │
│ • Files     │    │ • Aggregate │    │ • Files     │
│ • Webhooks  │    │ • Enrich    │    │ • APIs      │
└─────────────┘    └─────────────┘    └─────────────┘

n8n ETL Workflow

workflow: "Daily Sales ETL"
schedule: "2am daily"

nodes:
  # EXTRACT
  - name: "Extract from Shopify"
    type: shopify
    action: get_orders
    filter: created_at >= yesterday
    
  - name: "Extract from Stripe"
    type: stripe
    action: get_payments
    filter: created >= yesterday
    
  # TRANSFORM
  - name: "Merge Data"
    type: merge
    mode: combine_by_key
    key: order_id
    
  - name: "Transform"
    type: code
    code: |
      return items.map(item => ({
        date: item.created_at.split('T')[0],
        order_id: item.id,
        customer_email: item.email,
        total: parseFloat(item.total_price),
        currency: item.currency,
        items: item.line_items.length,
        source: item.source_name,
        payment_status: item.payment.status
      }));
      
  # LOAD
  - name: "Load to BigQuery"
    type: google_bigquery
    action: insert_rows
    table: sales_daily
    
  - name: "Update Google Sheets"
    type: google_sheets
    action: append_rows
    spreadsheet: "Daily Sales Report"

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Data Sources

Common Extractors