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Segment

Manage your data pipelines with Segment’s customer data platform for collecting, cleaning, and controlling customer data.

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Overview

The Segment skill provides comprehensive functionality for:

• Managing data warehouses and connections
• Creating and configuring data sources
• Setting up destinations for data routing
• Monitoring data pipeline health
• Integrating with various analytics and marketing tools

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Connection Requirements

This skill requires a Segment connection configured through Paragon Proxy.

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Basic Usage

// Create a new data warehouse
const warehouse = {
  "name": "Analytics Warehouse",
  "type": "snowflake",
  "connection": {
    "account": "my_snowflake_account",
    "warehouse": "COMPUTE_WH",
    "database": "ANALYTICS_DB",
    "schema": "PUBLIC",
    "username": "user",
    "role": "SYSADMIN"
  }
};

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Key Features

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Warehouse Management

• List Warehouses: View all configured data warehouses
• Create Warehouses: Add new warehouse connections (Redshift, BigQuery, Snowflake)
• Update Warehouses: Modify warehouse configurations
• Delete Warehouses: Remove warehouse connections

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Source Management

• List Sources: View all data sources in your workspace
• Create Sources: Add new data collection sources
• Update Sources: Modify source configurations
• Delete Sources: Remove data sources

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Destination Management

• List Destinations: View all configured destinations
• Create Destinations: Add new data destinations
• Update Destinations: Modify destination settings
• Delete Destinations: Remove destinations

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Common Operations

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Create a Data Warehouse

POST: warehouses
{
  "name": "Production Warehouse",
  "type": "redshift",
  "connection": {
    "host": "cluster.redshift.amazonaws.com",
    "port": 5439,
    "database": "analytics",
    "username": "admin",
    "schema": "public"
  }
}

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List All Sources

GET: sources

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Create a New Source

POST: sources
{
  "name": "Website Analytics",
  "slug": "website_analytics",
  "metadata": {
    "platform": "web",
    "categories": ["analytics"]
  }
}

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Update a Destination

PATCH: destinations/{destination_id}
{
  "name": "Updated Google Analytics",
  "metadata": {
    "platform": "web",
    "categories": ["analytics", "marketing"]
  }
}

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Supported Warehouse Types

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Redshift

{
  "type": "redshift",
  "connection": {
    "host": "cluster.redshift.amazonaws.com",
    "port": 5439,
    "database": "analytics",
    "username": "user",
    "schema": "public"
  }
}

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BigQuery

{
  "type": "bigquery",
  "connection": {
    "project_id": "my-gcp-project",
    "dataset": "analytics"
  }
}

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Snowflake

{
  "type": "snowflake",
  "connection": {
    "account": "my_snowflake_account",
    "warehouse": "COMPUTE_WH",
    "database": "ANALYTICS_DB",
    "schema": "PUBLIC",
    "username": "user",
    "role": "SYSADMIN"
  }
}

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Response Structure

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Warehouse Response

{
  "id": "warehouse_123",
  "name": "My Data Warehouse",
  "type": "redshift",
  "connection": {
    "host": "example.redshift.amazonaws.com",
    "port": 5439,
    "database": "analytics",
    "username": "user",
    "schema": "public"
  }
}

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Source Response

{
  "id": "source_123",
  "name": "Website Analytics",
  "slug": "website_analytics",
  "metadata": {
    "platform": "web",
    "categories": ["analytics"]
  }
}

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Destination Response

{
  "id": "destination_123",
  "name": "Google Analytics",
  "slug": "google_analytics",
  "metadata": {
    "platform": "web",
    "categories": ["analytics"]
  }
}

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Platform Categories

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Source Platforms

• web: Website tracking
• mobile: Mobile app analytics
• server: Server-side tracking
• cloud: Cloud application data

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Destination Platforms

• analytics: Analytics tools (Google Analytics, Mixpanel)
• marketing: Marketing platforms (Facebook Ads, Google Ads)
• crm: Customer relationship management
• email: Email marketing platforms

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Important Notes

• Slug Uniqueness: Source and destination slugs must be unique within your workspace
• Connection Security: Warehouse credentials are encrypted and stored securely
• Data Flow: Sources collect data, destinations receive processed data
• Real-time Processing: Segment processes data in real-time through configured pipelines
• Schema Management: Warehouse schemas are automatically managed by Segment

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Best Practices

1. Naming Conventions: Use descriptive names for sources, destinations, and warehouses
2. Environment Separation: Use different workspaces for development and production
3. Connection Testing: Test warehouse connections before deploying to production
4. Monitoring: Regularly monitor data pipeline health and delivery rates
5. Schema Evolution: Plan for schema changes in your data warehouse
6. Access Control: Implement proper access controls for sensitive data connections