> For the complete documentation index, see [llms.txt](https://docs.telm.ai/telmai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.telm.ai/telmai/connect-to-data/data-connections/google-bigquery.md).

# Google BigQuery

To set up a BigQuery connection, you need to specify the corresponding Google Project name. The Telmai service account must be granted access to the datasets requiring connections.

## Prerequisites

Before setting up the connection, identify which service account you will use:

* **Tenant service account** : Telmai's managed (or impersonated) service account. This is only available for GCP deployments. To find your specific tenant service account, open the **Create Connection** dialog and select BigQuery. The service account will be displayed on that page.
* **Your own service account**: if you prefer to provide your own credentials.

This service account must have the right permissions to access and query the data.

### Setting up permissions in Google BigQuery

1. Go to Google BigQuery and locate your project: `Google BigQuery / <project> / <dataset>`
2. Click **Share** or **Add Member**.
3. In the **New Member** field, enter the service account identified in the prerequisites above.
4. Assign the roles:
   1. `BigQuery Data Viewer`
   2. `BigQuery Metadata Viewer`
5. Save the settings.

### Setting up permissions in GCP Project

The used service account must also be granted `BigQuery Job User` in the GCP project where the query is expected to run

## Creating the connection in Telmai

BigQuery connections can be used to connect multiple data assets in Telmai using the same connection parameters. To add a BigQuery connection:

1. Navigate to Telmai connection page and click the **+ Add Connection** button.
2. In the **Create Connection** dialog, select **Google BigQuery** as the Connection Type.
3. Enter a **Name** for the connection (required) and an optional **Description**.
4. Under **Properties**, enter your **Google Project** name.
   * Optionally, check **Use dataset project for job** if you want the job to run under the dataset's project.
5. Under **Credentials**, select one of the following:
   * **Use service account credentials** - provide your own service account key.
   * **Use tenant service account** - uses the Telmai-managed service account.
6. Click **Create**.

<figure><img src="/files/fqvKM00omXEgdh023MWm" alt=""><figcaption></figcaption></figure>

## Connecting an asset

Once a connection is defined, you can start using it to create assets. To create assets, you will need:

* Dataset name
* \[Optional] Custom SQL

<figure><img src="/files/vXwyqEDkquPpajbZzvRD" alt=""><figcaption></figcaption></figure>