---
updatedAt: 2026-09-16T02:24:18.000Z
agentTools:
  projectIndex: https://docs.enterprise.appier.com/llms.txt
---

# BigQuery

BigQuery is a powerful data warehouse service on Google Cloud Platform (GCP), offering robust capabilities for large-scale data analytics. Integrating BigQuery with AIRIS enables you to unify your diverse data sources, creating a comprehensive foundation for customer insights.

Once you [connect BigQuery to your AIRIS account](#connect-bigquery-to-airis), you can [export data from AIRIS to BigQuery](#export-data-to-bigquery) for advanced analysis and reporting.

## Notes and limitations

Please note the following limitations when exporting data to BigQuery:

* Maximum number of rows: 10 million per table, per hour
* Maximum number of columns: 50 per table, per export
* To prevent performance issues, we strongly recommend limiting concurrent exports to 10 or less

In addition, the connected service requires time to process data before it's available for use, and this time can vary between different services. For example, a table with 5 million records and 50 columns can require 20-25 minutes to be fully uploaded and ready for use.

***

## 1. Connect BigQuery to AIRIS

To enable the integration, complete these setup steps:

1. [Create a BigQuery dataset and service account](#1-create-a-bigquery-dataset-and-service-account)
2. [Add the connection in the Appier console](#2-add-the-connection-in-the-appier-console)

### 1. Create a BigQuery dataset and service account

Before you can connect AIRIS to BigQuery, you need a dataset and service account with the appropriate permissions. Complete the following steps:

1. <Anchor label="Create a BigQuery dataset" target="_blank" href="https://cloud.google.com/bigquery/docs/datasets#create-dataset">Create a BigQuery dataset</Anchor>.
2. <Anchor label="Create a Google Cloud service account" target="_blank" href="https://cloud.google.com/iam/docs/service-accounts-create">Create a Google Cloud service account</Anchor>. Grant it the **BigQuery User** role at the project level.
3. <Anchor label="Create a new key for your service account" target="_blank" href="https://cloud.google.com/iam/docs/keys-create-delete#creating">Create a new key for your service account</Anchor> and download a private key in JSON format.
4. Return to the BigQuery console and <Anchor label="grant the service account dataset access permission" target="_blank" href="https://cloud.google.com/bigquery/docs/control-access-to-resources-iam#grant_access_to_a_dataset">grant the service account dataset access permission</Anchor>. Assign the following roles to the service account for the specific dataset:
   * **BigQuery Data Editor**
   * **BigQuery Data Viewer**

> 👍 Tip
>
> For optimal performance and data availability with AIRIS, we recommend that you select a **Multi-region** location when you create your BigQuery dataset.

### 2. Add the connection in the Appier console

In the Appier enterprise console, go to **Common settings** > **Partner integrations**, click **BigQuery**, then click **+ Connect BigQuery**.

<Image align="center" border={false} src="https://files.readme.io/43bc075a07f9877a76ca256f20a93881fb9255a1ff6cd0765fb7f1d03afdce63-integrations-bigquery.png" />

Enter a descriptive name for this connection and the BigQuery's account details, then click **Connect**:

* **Dataset ID**: The ID copied from BigQuery's console.
* **Service account key**: The downloaded account key.

<Image align="center" border={false} src="https://files.readme.io/225a47a7c5742c7cced1ce5ee038dc8e7bfc5402a56859924ce00ce0a85d8014-connect-bigquery.png" />

> 📘 Note
>
> To ingest your BigQuery data into AIRIS, see [BigQuery (AIRIS)](https://docs.airis.appier.com/docs/integrations-bigquery#/).

***

## 2. Export data to BigQuery

You can export reports from AIRIS to BigQuery in two ways:

* Click **Export** manually from an <Anchor label="activity report" target="_blank" href="https://docs.airis.appier.com/docs/activity-reports#exporting-and-sharing">activity report</Anchor> or <Anchor label="profile report" target="_blank" href="https://docs.airis.appier.com/docs/profile-reports#/exporting-and-sharing">profile report</Anchor> for one-time exports.
* Create a <Anchor label="scheduled batch" target="_blank" href="https://docs.airis.appier.com/docs/scheduled-batches#getting-started-with-scheduled-batches">scheduled batch</Anchor> to automatically export reports on a recurring basis.

### Export notes

* Large exports are processed in batches of 5 million records. You can see batches appear in BigQuery as they are processed.
* All fields are exported as strings. To convert data to other BigQuery data types, see <Anchor label="BigQuery's documentation" target="_blank" href="https://cloud.google.com/bigquery/docs/managing-table-schemas#change_a_columns_data_type">BigQuery's documentation</Anchor>.
* The resulting BigQuery tables are named using these formats:

| Export method                    | BigQuery table name                                                                   | Example                                 |
| :------------------------------- | :------------------------------------------------------------------------------------ | :-------------------------------------- |
| Scheduled batch                  | The name of the scheduled batch appended by the table creation time (Unix timestamp). | "daily\_customer\_activity\_1753276245" |
| Manual export (from report page) | The name of the report.                                                               | "campaign\_customer\_report"            |

### Troubleshooting

#### Permission denied (Error 403)

This is the most common export failure and occurs when your service account lacks the necessary BigQuery permissions. To resolve this issue, ensure your service account has:

* **BigQuery User role** at the project level
* **BigQuery Data Viewer** and **BigQuery Data Editor** permissions on the specific dataset.