---
title: "Google BigQuery connection guide"
slug: "google-bigquery-connection-guide"
description: "Connect your Google BigQuery data to Supermetrics with our guide. Learn about permissions, table IDs, and query types for seamless integration."
updated: 2026-07-08T09:01:07Z
published: 2026-07-08T09:01:07Z
canonical: "docs.supermetrics.com/google-bigquery-connection-guide"
stale: true
---

> ## Documentation Index
> Fetch the complete documentation index at: https://docs.supermetrics.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Google BigQuery connection guide

This guide contains all permissions and requirements for connecting your Google BigQuery data to Supermetrics.

You can connect to data sources from the [Data sources page on the Supermetrics Hub](https://hub.supermetrics.com/token-management). On the Hub, you can also [share an authentication link](https://docs.supermetrics.com/v1/docs/how-to-connect-to-data-sources-from-supermetrics-hub#share-authentication-link) to connect to a data source you don't have direct access to.

After you connect to the data source on the Hub, you can use the data source connection in [all available destinations](/docs/google-bigquery-connection-guide#connection-instructions).

## Required permissions

There are 2 ways to authenticate Google BigQuery: with OAuth 2.0, or with a service account.

****Permissions when connecting with OAuth 2.0****

You need a Google account with access to view and manage tables in BigQuery in Google Cloud in order to connect.

Required Google Account permissions:

- View and manage your tables, datasets, and jobs in Google BigQuery.
- See the email address for your Google Account.

****Permissions when connecting with a service account****

1. Create a service account:
  1. Create a service account and assign sufficient permissions for it, for example:

Detailed instructions are available in [Google’s documentation](https://docs.cloud.google.com/iam/docs/service-accounts-create#iam-service-accounts-create-console).
    1. roles/bigquery.user (project-level)
    2. roles/bigquery.dataViewer (dataset-level)
2. Create and obtain a private JSON key for the service account:
  1. In the Google Cloud console, go to the **Service accounts page**.
  2. Go to Service accounts and select a project.
  3. Click the email address of the service account you want to create a key for.
  4. Click the **Keys tab**.
  5. Click the **Add key** drop-down menu, then select **Create new key**.
  6. Select **JSON** as the Key type and click **Create**.
  7. To authenticate the connector, use the following values from the JSON file:

For more details on creating keys, refer to [Google’s documentation](https://docs.cloud.google.com/iam/docs/keys-create-delete).
    1. Private key: The complete string from `- - - - - BEGIN PRIVATE KEY - - - - -` to `- - - - - END PRIVATE KEY - - - - -\n`
    2. Key ID
    3. Client email

## Before you start the authentication process

### Obtain your table ID

1. Identify the BigQuery table you wish to connect to in the Google Cloud console.
2. In the left-hand Explorer section, click the three dots next to the table.
3. Select **Copy ID** and save this for later.

> [!NOTE]
> Note
> 
> The Table ID must be in the format `project.dataset.table` with exactly three dot-separated parts, such as`my-project.my_dataset.my_table`. A common mistake is copying only the project and dataset (such as `my-project.my_dataset`) without the table name. This will cause a "Not Found" error.

#### Sharded tables

Sharded tables are used, for example, for Google Analytics 4 events.

If your BigQuery dataset uses date-sharded tables (such as `events_20240101`, `events_20240102`, …), use a wildcard suffix `_*` to query all shards: `my-project.my_dataset.events_*`.

Entering a single shard like `events_20240101` queries only one day's data. Use it only if desired.

Don’t enter just the prefix without `_*` (such as `events`). This will fail with a "Table not found" error.

#### Example table IDs

Valid table IDs:

- `my-project.analytics_123456.events_*` (sharded/wildcard
- `my-project.my_dataset.orders` (single table)
- `my-project.my_dataset.daily_report_*` (sharded/wildcard)

Invalid table IDs:

- `my-project.my_dataset` (missing table name)
- `my-project.my_dataset.events_20240101` (single shard — use `events_*` instead)

#### Troubleshooting

| Error | Cause | Fix |
| --- | --- | --- |
| The table ID you inserted is incorrect | Table doesn't exist or the Table ID is missing the `_*` suffix for sharded tables. | Verify the table exists in BigQuery console. For sharded tables, add `_*` suffix. |
| Invalid Table ID | Table ID has fewer than 3 parts (missing table name). | Use format `project.dataset.table`. |
| Data Source Error: Not Found | DSU properties couldn't be resolved. | Re-connect with a valid 3-part Table ID. |

### Identify your date column

1. Select your table in the Google Cloud console and open the **Schema** tab.
2. Copy the field name of the column you want to use for date range filtering.

Please note that your BigQuery table must have a **DATE** or **DATETIME** column to fetch data for specific date ranges.

## Query types

If prompted, you need to select a query type to pull data.

- **Table**: Fetch data from your table in BigQuery.

## Connection instructions

****When connecting to Google BigQuery using OAuth 2.0****

1. You need to be logged in with your Google Account.
2. Select the Google BigQuery data source on the [Supermetrics Hub](https://hub.supermetrics.com/) or in the data destination.
3. Insert the **table ID**.
4. If prompted, choose to make this connection [shared or private](https://docs.supermetrics.com/docs/about-shared-and-private-connections).
5. Click **Start**.
6. In your data destination, fill in the value for the **Date column** setting.

****When connecting to Google BigQuery using a service account****

1. Select the Google BigQuery data source [on the Supermetrics Hub](https://hub.supermetrics.com/token-management) or in the data destination.
2. Insert the **table ID**, **Private key**, **Key ID**, and **Client email**.
3. If prompted, choose to make this connection [shared or private](https://docs.supermetrics.com/docs/about-shared-and-private-connections).
4. Click **Start**.
5. In your data destination, fill in the value for the **Date column** setting.

See detailed instructions on [how to connect to a data source from the Supermetrics Hub](https://docs.supermetrics.com/docs/how-to-connect-to-data-sources-from-supermetrics-hub).

You can also connect to Google BigQuery from these destinations:

- Google Sheets: [How to connect to a Supermetrics data source in Google Sheets](https://docs.supermetrics.com/docs/how-to-connect-to-a-supermetrics-data-source-in-google-sheets)
- Data Studio: [How to connect data sources to Data Studio](/v1/docs/how-to-connect-data-sources-to-data-studio)
- Excel: [How to connect data sources to Excel with Supermetrics](https://docs.supermetrics.com/docs/how-to-connect-data-sources-to-excel-with-supermetrics)
- Power BI: [How to create your first Supermetrics query for Power BI](https://docs.supermetrics.com/docs/how-to-create-your-first-supermetrics-query-for-power-bi)
- The Supermetrics API: [How to use the Query Manager](https://docs.supermetrics.com/docs/how-to-use-the-query-manager)
- Data warehouse and cloud storage (Hub): [How to create a transfer](https://docs.supermetrics.com/docs/how-to-create-a-transfer)

## More resources

- [How to reauthenticate a data source connection](/v1/docs/how-to-reauthenticate-a-data-source-connection)
- [How to manage data source connections on the Supermetrics Hub](https://docs.supermetrics.com/docs/how-to-manage-data-source-connections-on-supermetrics-hub)