Renta
  • Product
    Product
    • First-party tracking

      Powerful server-side solution for collect and connect customer data

    • Marketing ETL

      Create secure customer’s data pipelines to any data warehouses

    • ETL Add-on for Google Sheets

      The easiest way to collect your marketing data into spreadsheets

  • Resources
    Resources
    • Blog

      Stories on how to use customer data for company growth

    • Documentation

      Learn how to install, set up, and use Renta tools.

  • Pricing
  • Book a demo
  • Sign in
Sign up for free
  • Product
    Product
    • First-party tracking

      Powerful server-side solution for collect and connect customer data

    • Marketing ETL

      Create secure customer’s data pipelines to any data warehouses

    • ETL Add-on for Google Sheets

      The easiest way to collect your marketing data into spreadsheets

  • Resources
    Resources
    • Blog

      Stories on how to use customer data for company growth

    • Documentation

      Learn how to install, set up, and use Renta tools.

  • Pricing
  • Book a demo
  • Sign in
Sign up for free
Renta
Documentation
ETL destinations
Google BigQuery Destination
  • Integration creating in data warehouse (DWH)

Google BigQuery Destination

BigQuery is a fully managed enterprise data warehouse that helps you manage and analyze your data reports.

With BigQuery, you can use standart SQL queries to run your analytics.

Renta can use Google BigQuery as Destination and import data into it.

In order to add Google BigQuery to Renta, you'll need:

  • Already created Google Cloud Platform project. How to create it

  • The user that has BigQuery Admin and Storage Admin roles for the GCP project

  • Active billing in the GCP system.

Short guide to create your first pipeline with Google BigQuery:

Integration creating in data warehouse (DWH)

  1. Go to the second step of creating pipeline with any source

  2. Select Google BigQuery

  3. Complete authentication to your GCP account

  4. Authorize Renta in order to have access to your data

  5. Specify the project ID

  6. And the Dataset

  7. Select the added dataset in order to continue to create your pipeline.