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Understand Data Warehouse Automation for Google BigQuery

You can use the Data Warehouse Automation for Google BigQuery to send data from any source application into Google BigQuery. The Data Warehouse Automation for Google BigQuery allows you to easily create exports from some sources with minimal configuration, for other source applications, additional configuration steps may be required. By default, the following apps are supported out-of-the-box to have the entire flow configured (including the export configuration).

  • BigCommerce:
    • Retrieve a list of orders (delta)
    • Retrieve a list of products (delta)
    • Retrieve all customers (delta)
    • Retrieve all transactions (delta)
    • Retrieve subscribers (delta)
  • Hubspot:
    • Get recently created contacts (all export)
    • Get recently created deals (delta)
    • Get recently modified companies (delta)
    • Search for products (delta)
  • Loop Returns: Return details (all export)
  • Magento:
    • Customer group search (all export)
    • Product search (delta)
    • Search sales order (delta)
    • Search transactions (all export)
    • Search returns (all export)
  • Mailchimp:
    • Retrieve all campaigns (delta)
    • Retrieve campaign reports (delta)
    • Retrieve a list of automations (delta)
  • Returnly: Retrieve collection of RMAs (delta)
  • Shopify (use as example):
    • Retrieve a list of orders (delta)
    • Retrieve abandoned checkouts (delta)
    • Retrieve a list of products (delta)
    • Retrieve a list of all payouts ordered by payout date (delta)
  • Zendesk:
    • Search API for tickets (delta)
    • Show many users (all export)
    • Show many organizations (all export)

Features & benefits

  • Stay in compliance by improving data accuracy, minimizing wrong or duplicate records
  • Reduce maintenance time with an interactive dashboard for sophisticated error handling and integration support
  • Efficiently scale operations by automating processes that rely on the Google BigQuery platform
  • Take control of your integrations with tools that let you configure and make mapping changes on the fly

Supported integration flows

The Data Warehouse Automation for Google BigQuery contains workflows that you can easily configure and deploy without coding or IT support. The following built-in flows export data from the specified source data to Google BigQuery.

Configured and unconfigured flows to Google BigQuery

Flow name
Source application export to Google BigQuery
Source application to Google BigQuery production table - Merge & Delete

Error handling

If you encounter any of the following errors, use the steps provided to resolve them.

  • The General Settings page has an empty drop-down menu and displays no connections. Navigate to the Connections tab to create and register your connections. You can only use registered connections with Data Warehouse Automation for Google BigQuery.
  • integrator.io displays one of the following error messages:
    • "SQL compilation error: error line 1 at position 101\ninvalid identifier 'COLUMN3'". Verify the resource ID for your export is correct.
    • "SQL compilation error:\nTable 'TEMPTABLE' does not exist or not authorized." Open the Source application export to Google BigQuery flow and enter a temporary table name to be created in Google BigQuery.
    • AsyncHelpers#resolveIds() expects a string. Open the Source application to Google BigQuery production table - Merge & Delete flow and verify that both temporary and production table names have been entered.

Most integrator.io error messages will clearly explain the error and suggest troubleshooting methods. If you are unsure of what the error means, contact Celigo support.

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