Phiona Documentation
  • 👋Introduction
  • 🛣️The Basics
    • How Phiona Works
    • Scheduling & Automation
    • API Documentation
  • 🔗Data Sources
    • Airtable
    • Amazon S3
    • BigCommerce
    • BigQuery
    • Dropbox
    • Firebase
    • Google Analytics v4
    • Google Drive
    • Google Search Console
    • Google Sheets
    • Hubspot
    • Import from API (Beta)
    • Local Files
    • MongoDB
    • MySQL
    • PostgreSQL
    • Redshift (Beta)
    • Shopify
    • Snowflake (Beta)
    • WooCommerce
    • Wordpress
  • 📈Sharing Data
    • Share Project with Collaborators
    • Share Public Project Link
    • Share Serverless SQL Warehouse
    • Build API Endpoint From Single Dataset
    • Share Dataset via Email
  • 🛠️Clean & Transform
    • Supported Data Types & Column Header Functions
    • Supported Clean Functions
    • Supported Transformations
    • Applying Existing or Shared Blueprints
  • 🌆Export Destinations
    • Airtable
    • Amazon S3
    • Dropbox
    • Google Drive
    • Google Sheets
    • MongoDB
    • MySQL
    • PostgreSQL
    • Redshift (Beta)
    • Snowflake (Beta)
  • Changelog
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  1. Export Destinations

Snowflake (Beta)

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Last updated 3 years ago

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To export your datasets to Snowflake, you'll click on the Export button in either the sidebar or on your data tile. Once you get to the Export screen, select Snowflake from the dropdown.

You'll then select the connection and database that you would like to export to.

If the table name that you are exporting is unique within the Snowflake database, it will create a new table. However, if the table name already exists (say it's on a regular schedule, etc), you have one of two options.

The first is to drop (remove) the original table in Snowflake to replace it with your new data from Phiona. This might be good for a daily report, or a situation where your data needs to be updated regularly.

The second option is to keep the existing table, and rename your dataset as it leaves Phiona to something different.

🌆
Select Snowflake