---
title: "BigQuery Configuration"
slug: "bigquery-configuration"
updated: 2026-01-12T16:36:23Z
published: 2026-01-12T16:36:23Z
---

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

# BigQuery Configuration

> {{variable.Who can use this}} {{glossary.Tech admin}}
> {{variable.Available on}} {{glossary.Data Cloud}}

## Step 1: Create service account in BigQuery project

1. In the GCP console, navigate to the **IAM & Admin** menu, click into the **Service Accounts** tab, and click **Create service account** at the top of the menu.
2. In the first step, name the user and click **Create and Continue**.
3. In the second step, grant the user the role **BigQuery User**.

![](https://storage.googleapis.com/prequel_docs/images/gcp-bigquery-user.png)

> 📘 **Understanding the BigQuery User role**
>
> The BigQuery User role is a predefined IAM role that allows for the creation of new datasets, with the creator granted BigQuery Data Owner on the new dataset.
>
> If you would like to avoid using the BigQuery User role, the minimum required permissions are:
> - On the **Project level**:
>   - `bigquery.datasets.create`
>   - `bigquery.datasets.get`
>   - `bigquery.jobs.create`
>
> *Note: These minimum permissions assume that the dataset has not been created ahead of time. If you create the dataset ahead of time, see the following note.*

> 📘 **Loading data into a Dataset that already exists**
>
> By default, a new dataset (with a name you provide) will be created in the BigQuery project. If instead you create the dataset ahead of time, you will need to grant the **BigQuery Data Owner** role to this Service Account at the dataset level.
>
> In BigQuery, click on the existing dataset. In the dataset tab, click **Sharing**, then **Permissions**. Click **Add Principals**. Enter the Service Account name, and add the Role: **BigQuery Data Owner**
>
> Specifically, the minimum permissions required can be granted to the principal and applied to the **Dataset**:
> - `bigquery.tables.create`
> - `bigquery.tables.delete`
> - `bigquery.tables.get`
> - `bigquery.tables.getData`
> - `bigquery.tables.list`
> - `bigquery.tables.update`
> - `bigquery.tables.updateData`
> - `bigquery.routines.get`
> - `bigquery.routines.list`
>
> On the **Project** level, you will still need `bigquery.jobs.create`, but you will not need `bigquery.datasets.create` or `bigquery.datasets.get`.

4. In the third step (**Grant users access to this service account** step), click **Done**.
5. Back in the **Service accounts** menu, click the **Actions** dropdown next to the newly created service account and click **Manage keys**.
![](https://storage.googleapis.com/prequel_docs/images/gcp-manage-service-account-keys.png "manage sa keys.png")
6. Click **Add key** and then **Create new key**.
![](https://storage.googleapis.com/prequel_docs/images/gcp-create-new-key.png "create new key sa.png")
7. Select the **JSON** Key type and click **Create** and make note of the key that is generated.


## Step 2: Create a staging bucket

1. Log into the Google Cloud Console and navigate to **Cloud Storage**. Click **Create** to create a new bucket.

![](https://storage.googleapis.com/prequel_docs/images/gcp-create-gcs-bucket.png)

2. Choose a **name** for the bucket. Click **Continue**. Select a **location** for the staging bucket. Make a note of both the **name** and the **location** (region).

> 📘 **Choosing a `location` (region)**
>
> The location you choose for your staging bucket must match the location of your destination dataset in BigQuery. When creating your bucket, be sure to choose a region in which BigQuery is supported [(see BigQuery regions)](https://cloud.google.com/bigquery/docs/locations)
>
> - If the dataset **does not** exist yet, the dataset will be created for you in the same region where you created your bucket.
> - If the dataset **does** exist, the dataset region must match the location you choose for your bucket.

3. Click **continue** and select the following options according to your preferences. Once the options have been filled out, click **Create**.
4. On the **Bucket details** page that appears, click the **Permissions** tab, and then click **Add**.

![](https://storage.googleapis.com/prequel_docs/images/gcp-add-permission-to-bucket.png)

5. In the **New principles** dropdown, add the Service Account created in **Step 1**, select the **Storage Admin** role, and click **Save**.

![](https://storage.googleapis.com/prequel_docs/images/gcp-storage-admin.png)

> 📘 **Understanding the Storage Admin role**
>
> The **Storage Admin** role is a predefined IAM roles that allow for the creation of new storage objects and reading of those objects when loading into BigQuery. If you would like to avoid using the **Storage Admin** role, the minimum required permissions are:
>
> - storage.buckets.get
> - storage.objects.create
> - storage.objects.delete
> - storage.objects.get
> - storage.objects.list


## Step 3: Connect Gong to BigQuery
Once you have configured BigQuery, use the fields to set up the connection in Gong: 

1. In Gong, go to **Admin center** > **Settings** > **Data Cloud** > **Data cloud settings**.
2. Select **BigQuery**
3. Enter the following details
    * **Project ID**
    * **Dataset**
    * **Bucket name**
    * **Bucket region**
    * **Service account email**
    * **Service account JSON key**
4. Click **Connect**. It may take a few minutes to complete the connection.

## Related

- [Database design](/database-design.md)
- [Forecast and Gong user tables](/forecast-and-gong-user-tables.md)