Google BigQuery destination

Learn how to connect your Google BigQuery data warehouse as a destination in Renta ELT.

Prerequisites

Before you begin, ensure you have:

1. A Google Cloud Platform (GCP) project.
2. Access to the Renta ELT platform.

Required roles

Grant both roles below to the identity that connects to Renta: the service account or the Google account you sign in with. Grant them at the project level, not on a single dataset.

Which dataset Renta uses

When you connect with a service account, Renta picks the dataset the destination writes into:

1. If the project has a dataset named Renta_dataset, Renta uses it.
2. If the project has other datasets, Renta uses the first one by name and creates nothing. Change it in BigQuery dataset after the connection is created.
3. If the key sees no dataset at all, Renta creates Renta_dataset in the selected Data Location, so that the project has somewhere to load data into.

Creating a dataset needs the bigquery.datasets.create permission, and the BigQuery Data Editor role grants it only at the project level. In an empty project a key with dataset-level access fails with the message User does not have bigquery.datasets.create permission in project <project ID>.

Dataset-level access

If your security policy does not allow project-level data access, give the service account access to the datasets it needs and nothing else:

1. In your project, create the dataset for Renta if it does not exist yet, for example Renta_dataset. Choose the location you will select in Renta.
2. Grant the service account the BigQuery Data Editor role on that dataset.
3. Grant the service account the BigQuery Job User role at the project level. Jobs always run at the project level, so this role has no dataset-level alternative.

Renta uses the dataset the key can see and creates nothing.

Adding Google BigQuery destination via service account

Navigate to DestinationsStep 1

Log in to your Renta ELT platform and navigate to the Destinations section in the left sidebar. Click the + Add destination button in the top right corner.

Select Google BigQueryStep 2

In the Destination catalog, find and select Google BigQuery from the list of available destinations.

Select Service AccountStep 3

Select GCP Service Account as the authorization method. This is the recommended method for production environments.

In Data Location, select the region or multi-region for Renta_dataset. Renta creates the dataset there only if the project has no dataset yet. This field is optional.

Click Upload a Service Account JSON file and select the JSON key file you generated in the Google Cloud Console. Renta reads the project ID from the key and checks that the key reaches the project and the dataset.

Configure the destinationStep 4

After uploading the key, the project ID will be automatically detected (or you may need to confirm it). Fill in the remaining configuration details:

Field	Description
Destination name	Specify a name for this destination (e.g., Marketing Data Warehouse).
BigQuery project	The project ID from your Service Account.
BigQuery dataset	The dataset Renta loads data into. After the upload it is Renta_dataset or the first existing dataset of the project. Pick another dataset if the service account has access to it.
Data Location	(Optional) The location of Renta_dataset. Renta creates the dataset there only when the key sees no dataset in the project.

Click Save to complete the setup.

Verify the connectionStep 5

You will be redirected to the list of destinations. Verify that your new BigQuery destination appears in the list with an Active status.

Adding Google BigQuery Destination via OAuth

Navigate to DestinationsStep 1

Log in to your Renta ELT platform and navigate to the Destinations section in the left sidebar. Click the + Add destination button in the top right corner.

Select Google BigQueryStep 2

In the Destination catalog, find and select Google BigQuery from the list of available destinations.

Authenticate with GoogleStep 3

Select Authenticate with Google Account as the authorization method. This option allows you to connect quickly using your personal access.

Click the Log in to your Google BigQuery account button to proceed.

Grant accessStep 4

A Google authentication window will appear. Select your Google account and click Allow to grant Renta the necessary permissions to manage data in BigQuery.

Configure the destinationStep 5

After successful authentication, fill in the configuration form:

Field	Description
Destination name	Specify a name for this destination (e.g., Marketing Data Warehouse). This is used exclusively in the Renta interface.
BigQuery project	Select the Google Cloud project you want to use.
BigQuery dataset	Select an existing dataset or create a new one where the data will be loaded.
Data Location	(Optional) Select the geographic location for your dataset. If there are no datasets in the project, a Renta_dataset will be created in the specified region.

Click Save to complete the setup.

Verifying the connection

After saving the destination, you will be redirected to the list of destinations. You can now use this Google BigQuery connection when creating pipelines.

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