# BigQuery BigQuery is Google Cloud Platform's analytical data warehouse. Euno's BigQuery integration discovers resources from BigQuery metadata and query history so teams can understand warehouse structure, lineage, and usage. Euno's BigQuery integration supports auto-discovery of: * GCP projects * BigQuery databases and datasets * BigQuery tables, views, materialized views, external tables, snapshots, and clones * BigQuery columns, including nested STRUCT fields * Google Sheets referenced by BigQuery external tables * BigQuery usage, cost, and lineage properties from query history * Hex project usage and lineage from BigQuery query history * Optional Sigma usage from BigQuery query history ## Prerequisites Before you configure the integration, make sure you have: * A GCP project that Euno can use to run BigQuery metadata queries. This is the execution project. * The list of GCP projects Euno should discover. These are the discovered projects. * Permission to create a GCP service account and service account key. * Permission to grant IAM roles on every discovered project. * The BigQuery regions where Euno should scan query history, for example `us`, `eu`, or `us-central1`. To discover BigQuery resources, Euno queries system-defined, read-only [INFORMATION\_SCHEMA](https://cloud.google.com/bigquery/docs/information-schema-intro) views. A BigQuery query runs under one project and can access tables and views in other projects, so the execution project can be different from the discovered projects. ```mermaid graph LR exe[execution project] --> dis1[discovered project 1] exe --> dis2[discovered project 2] euno[Euno integration] -->|run queries| exe ``` ## Stage 1: Configure GCP ### Step 1: Create a GCP Service Account on the Execution Project 1. In GCP, choose the execution project. 2. Browse to the [Service Accounts](https://console.cloud.google.com/iam-admin/serviceaccounts) page. 3. Click **Create service account**. 4. Enter a service account name, for example `Euno BigQuery Integration`. 5. Copy the service account email address, for example `euno-bigquery-integration@my-project.iam.gserviceaccount.com`. 6. Click **Create and continue**. 7. Under **Permissions**, choose the **BigQuery User** role. The technical identifier is `roles/bigquery.user`. 8. Click **Continue**, then click **Done**. ### Step 2: Create a Service Account Key 1. Go to the service account page for the service account you created. 2. On the **Keys** tab, click **Add key**, then click **Create new key**. 3. Choose **JSON** as the key type. 4. Click **Create** and save the file. ### Step 3: Grant Access to Discovered Projects For each discovered project: 1. Browse to the project's [IAM configuration](https://console.cloud.google.com/iam-admin/iam). 2. Click **Grant access**. 3. Under **New principals**, enter the service account email address from Step 1. 4. Under **Assign roles**, choose **BigQuery Metadata Viewer**. The technical identifier is `roles/bigquery.metadataViewer`. 5. Click **Add another role** and choose **BigQuery Resource Viewer**. The technical identifier is `roles/bigquery.resourceViewer`. 6. Click **Save**. ## Stage 2: Configure New BigQuery Source in Euno ### Step 1: Access the Sources Page In Euno, open the **Sources** page and click **Add New Source**. Select **BigQuery**. ### Step 2: General Configuration Asterisk (\*) means a mandatory field. | Configuration | Description | | --------------------------- | --------------------------------------------------------------------------------------------------------------------------- | | **Service Account Key**\* | Copy the entire contents of the service account key JSON file and paste it here. | | **Query History Regions**\* | Comma-separated list of BigQuery regions to scan for query history, for example `us-east1,us-west1`. | | **Execution Project ID** | GCP project ID used as the execution project. If not specified, Euno uses the project where the service account is defined. | | **Query Location** | BigQuery location where Euno should run queries. | ### Step 3: Advanced Settings Click **Advanced** to display additional configurations. | Configuration | Description | | --------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | **Discover dataset labels as meta** | Discover [BigQuery dataset labels](https://cloud.google.com/bigquery/docs/labels-intro) as `meta` values for BigQuery dataset resources. Defaults to disabled. | | **Auto discover Sigma usage from BigQuery query history** | Detect Sigma SQL footers in BigQuery query history and use them to populate Sigma usage. | | **Sigma usage lookback (days)** | Number of days to look back when detecting Sigma usage from BigQuery query history. Defaults to `7`. | | **Cost per slot per hour (USD)** | Cost used for BigQuery cost calculations. Defaults to `0.04`. | | **Project Discovery Pattern** | Use regular expressions to allow or exclude specific GCP projects. `.*` includes or excludes all projects. | | **Column Observation - Dataset Pattern** | Use regular expressions to allow or exclude specific datasets from column observation. `.*` includes or excludes all datasets. | | **Column Observation - Table Pattern** | Use regular expressions in `dataset.table` format to allow or exclude specific tables from column observation. For example, `bq_log\..*` excludes all tables in the `bq_log` dataset. | ### Step 4: Schedule * Enable the Schedule option. * Choose: 1. **Weekly**: Set specific days and times. 2. **Hourly**: Define the interval in hours, for example every 8 hours. ### Step 5: Resource Cleanup * **Immediate Cleanup**: Remove resources not detected in the most recent successful source run. * **No Cleanup**: Keep all resources indefinitely, even if they are no longer detected. To keep your data relevant and free of outdated resources, Euno provides automatic **Resource Cleanup** options. These settings determine when a resource should be removed if it is no longer detected by a source run. For a detailed explanation, see [Resource Sponsorship in Euno](/developer-reference/technical-concepts/resource-sponsorship-and-cleanup-in-euno.md). ### Step 6: Save Configuration Click **Test & Save** to complete the setup. ## What Euno Discovers Euno discovers BigQuery resources including GCP projects, databases, datasets, tables, columns, Google Sheets referenced by external tables, and Hex projects detected from BigQuery query history. For detailed information about discovered resources and their properties, see [BigQuery Integration Discovered Resources](/sources/data-warehouses/bigquery-integration/bigquery-integration-discovered-resources.md). --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://docs.euno.ai/sources/data-warehouses/bigquery-integration.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.