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

# Google BigLake (Iceberg)

The Google BigLake integration in Elementary allows you to automatically monitor volume & freshness anomalies in your Iceberg tables managed by a BigLake Metastore catalog, by continuously syncing metadata about Iceberg snapshots.

<Note>
  BigLake Iceberg is only supported for BigQuery environments. The same service account used for your BigQuery warehouse connection is reused — no separate credentials are required.
</Note>

## GCP Setup

### 1. Grant additional IAM roles

Elementary reuses the service account that is already connected to your BigQuery environment. You only need to grant three additional roles to that service account:

**On the GCP project that owns the BigLake catalog:**

| Role                                                            | Purpose                                                                    |
| --------------------------------------------------------------- | -------------------------------------------------------------------------- |
| `roles/biglake.metadataViewer`                                  | Allows listing namespaces and tables in the BigLake Metastore catalog      |
| `roles/serviceusage.serviceUsageConsumer`                       | Required for the BigLake REST API to attribute quota usage to your project |
| `roles/storage.objectViewer` (with condition — explained below) | Grants read access to Iceberg metadata files in GCS                        |

### 2. Scope the Storage Object Viewer role to metadata files only

For security, restrict the `Storage Object Viewer` role to Iceberg metadata files rather than granting access to all objects in the bucket.

When assigning the role on the GCS bucket, add a **condition**:

```json theme={null}
{
  "expression": "resource.name.endsWith(\".metadata.json\")",
  "title": "Iceberg metadata files only"
}
```

This ensures the service account can only read `*.metadata.json` files — the Iceberg snapshot metadata — and nothing else in the bucket.

## Elementary Configuration

Navigate to **Account settings > Environments**, choose your BigQuery environment, and scroll to the **Metadata Layer** section. Select **BigLake**.

### Connection Settings

| Field                | Required | Description                                                                                                |
| -------------------- | -------- | ---------------------------------------------------------------------------------------------------------- |
| **Connection Name**  | Yes      | A descriptive name for this connection (e.g. "Data Lake"). Must be unique if adding multiple integrations. |
| **Catalog name**     | Yes      | The name of your BigLake Metastore catalog.                                                                |
| **GCP project**      | No       | Only required if the BigLake catalog is in a different GCP project than your connected BigQuery warehouse. |
| **Catalog location** | No       | Only required if the BigLake catalog is in a different GCP region than your connected BigQuery dataset.    |