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Overview

This guide walks you through connecting your Google BigQuery data warehouse to Permutive so you can import data for audience building and activation. BigQuery is one of the simplest sources to connect — you just need to grant Permutive access to your dataset and provide your project and dataset details.
Prerequisites:
  • A Google Cloud Platform (GCP) account with BigQuery enabled
  • Access to manage IAM permissions on your BigQuery dataset
  • Knowledge of your GCP Project ID and Dataset name

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Step 1: Grant Permutive Access to Your Dataset

Before creating the connection in Permutive, you need to grant read access to your BigQuery dataset.
1

Open Your BigQuery Dataset

In the Google Cloud Console, navigate to BigQuery and select the dataset you want to connect to Permutive.
2

Open Sharing Settings

Click on the dataset name, then click Sharing > Permissions.
3

Add Permutive Service Account

Click Add Principal and enter the following service account email:
[email protected]
4

Assign the Required Role

Assign the following role to the service account:
  • BigQuery Data Viewer (roles/bigquery.dataViewer)
This grants Permutive read-only access to the tables within your dataset.
5

Save

Click Save to apply the permissions.
For more details on configuring BigQuery IAM roles, see Google’s documentation on BigQuery access control.

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Step 2: Find Your Project ID and Dataset Name

You’ll need two pieces of information from your GCP account:

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GCP Project ID

  1. In the Google Cloud Console, click on the project dropdown at the top of the page
  2. Your Project ID is displayed next to each project name
  3. Alternatively, go to IAM & Admin > Settings to see the Project ID

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Dataset Name

  1. In BigQuery, expand your project in the Explorer panel
  2. The Dataset Name is shown directly under your project
The Project ID and Dataset Name are case-sensitive. Ensure you enter them exactly as they appear in your GCP account.

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Step 3: Create the Connection in Permutive

1

Select BigQuery from the Catalog

In the Permutive dashboard, go to Connectivity > Catalog and select Google BigQuery. Click Connect.
2

Enter Connection Details

Fill in the following fields:
FieldDescription
NameA descriptive name for your connection in Permutive. This is for your reference only.
GCP Project IDThe Project ID from your GCP account (must match exactly)
GCP Dataset NameThe Dataset name from your BigQuery account (must match exactly)
ConfirmationConfirm that you’ve granted [email protected] the roles/bigquery.dataViewer role on your dataset
3

Save the Connection

Click Save to create the connection. It will appear on your Connections page with a “Processing” status while Permutive validates access to your dataset. Once validated, the status changes to “Active”.

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Step 4: Create an Import

Once your connection is active, you can create imports to bring data into Permutive.
1

Navigate to Imports

Go to Connectivity > Imports and click Create Import.
2

Configure the Import

  1. Select Google BigQuery as the source type
  2. Select your BigQuery connection
  3. Choose the table you want to import
  4. Continue with the standard import configuration
For more details on configuring imports, see Imports.

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Troubleshooting

If your connection remains in “Processing” status or fails:
  • Verify that [email protected] has been granted the roles/bigquery.dataViewer role
  • Check that the Project ID and Dataset Name are entered exactly as they appear in GCP (case-sensitive)
  • Ensure the dataset exists and contains tables
Solution: Double-check IAM permissions in the Google Cloud Console and verify your Project ID and Dataset Name.
If you receive permission errors after creating the connection:
  • The service account may not have been granted access correctly
  • The role may have been applied at the wrong level (project vs dataset)
Solution: Ensure the roles/bigquery.dataViewer role is granted specifically on the dataset you’re connecting to, not just at the project level.
If you don’t see expected tables after creating the connection:
  • Verify the dataset contains tables (not just views, if views aren’t supported)
  • Check that permissions are applied to the correct dataset
Solution: Review your dataset in BigQuery to confirm tables exist and permissions are correctly configured. After updating permissions, run a schema resync in Permutive to refresh the available tables. To access the resync option, go to Create Import, enter an import name, select the source, and select the connection—the Resync with source button will then appear.
If you entered incorrect values:
  • You’ll need to create a new connection with the correct values
  • The existing connection cannot be edited
Solution: Create a new connection with the correct Project ID and Dataset Name.

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FAQ

Permutive only requires read access to your data. The roles/bigquery.dataViewer role grants:
  • Read access to the dataset’s metadata
  • Read access to all tables within the dataset
Permutive cannot modify, delete, or write data to your BigQuery dataset.
Yes, you can create separate connections for each dataset you want to import from. Each connection requires its own IAM configuration.
Yes, you can create connections to datasets across multiple GCP projects. Ensure [email protected] has the required permissions on each dataset.
Permutive supports standard BigQuery tables. Partitioned tables are also supported.

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Next Steps

Create an Import

Learn how to import data from your BigQuery connection

Back to Sources

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