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Set up Cloud Billing data export to BigQuery

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This document provides all required setup steps to set up Cloud Billing data export to BigQuery.

To export Cloud Billing data to BigQuery, take the following steps:

• Create a project where the Cloud Billing data will be stored, and enable billing on the project (if you haven't already done so).
• Configure permissions on the project and on the Cloud Billing account.
• Enable the BigQuery Data Transfer Service API (required to export your pricing data).
• Create a BigQuery dataset to store the data in.
• Enable Cloud Billing export of cost data and pricing data to be written into the dataset.

This document walks you through the details of each of these steps.

The Google Cloud console (visit documentation, open console) is a web UI used to provision, configure, manage, and monitor systems that use Google Cloud products. You use the Google Cloud console to set up and manage Google Cloud and Cloud Billing resources.

To enable and configure the export of Google Cloud billing usage cost data to a BigQuery dataset, you need the following permissions:

• For Cloud Billing, you need either the Billing Account Costs Manager role or the Billing Account Administrator role on the target Cloud Billing account.
• For BigQuery, you need the BigQuery User role for the Google Cloud project that contains the BigQuery dataset to be used to store the Cloud Billing data.

To enable and configure the export of Cloud Billing pricing data and CUD metadata, you need the following permissions:

• For Cloud Billing, you need the Billing Account Administrator role on the target Cloud Billing account.
• For BigQuery, you need the BigQuery Admin role for the Google Cloud project that contains the BigQuery dataset to be used to store the Cloud Billing pricing data.
• For the Google Cloud project containing the target dataset, you need the resourcemanager.projects.update permission. This permission is included in the roles/editor role.

You might also need other project permissions. If you're a member of a Google Cloud Organization, to create a new project, you need the Project Creator role on the Organization or Folder. Specifically, to create a new project, you need the following permissions:

• resourcemanager.organizations.get
• resourcemanager.projects.create

For more information about Google Cloud permissions, see:

• Overview of Cloud Billing access control
• Create custom roles for Cloud Billing
• Understanding Predefined Identity and Access Management Roles

• If you have VPC Service Controls enabled for BigQuery resources on your project or organization, you will need to create ingress and egress rules to properly enable this export:

  • Create an ingress rule that gives the individual access to create the export:

  - ingressFrom:
      identities:
      - PRINCIPAL_ID_FOR_PERSON_ENABLING_SUBSCRIPTION
      sources:
      - accessLevel: "*"
  ingressTo:
      roles:
      - roles/bigquery.dataOwner
      resources:
      - projects/YOUR_PROJECT_ID_TO_HOST_SAMPLE_DATA
  title: 'Sample Export Ingress'
  

  • Create an egress rule to enable Google Cloud to create the BigQuery Linked Dataset within the VPC-SC:

  - egressTo:
      roles:
      - roles/bigquery.dataOwner
      resources:
      - projects/710382390241
  egressFrom:
      identityType: ANY_IDENTITY
      sources:
      - accessLevel: "*"
      sourceRestriction: RESTRICTION_STATUS
  title: 'Sample Export Egress'
  

  Note: If you skip this step, you will receive the following error when you attempt to enable the sample export: You don't have permissions to enable the same dataset.

Get started with billing data exports using this interactive tutorial. In the tutorial, you'll enable Cloud Billing data to export to a BigQuery dataset. Next, you'll run some sample queries through the BigQuery web interface to examine billing data.

Complete the five steps in this section to enable the export of your Cloud Billing data to BigQuery.

For a quick introduction to enabling billing data export and running sample queries of Cloud Billing data in BigQuery, follow this interactive tutorial for billing data export.

If you're a reseller, you can set up a reseller-specific export of your Channel Services billing data using the Partner Sales Console. To do so, follow steps 1-4 on this page to create your project and BigQuery dataset. Then for step 5, see Export Channel Services data to BigQuery to enable the export.

Cloud Billing data exported to BigQuery is contained in a BigQuery dataset. A dataset is contained within a Google Cloud project you specify.

We recommend that you create and use a separate Google Cloud project to contain all of your FinOps and billing administration needs for a Cloud Billing account, including your exported Cloud Billing data. Learn more about the benefits to using a FinOps-focused project for your billing administration use cases.

In the Google Cloud console, on the project selector page, select or create a Google Cloud project.

Go to project selector

Learn more about creating and managing projects.

You must make sure that billing is enabled on the Google Cloud project you select to contain your dataset, and that the Google Cloud project is linked to the same Cloud Billing account that contains the data that you plan to export to the BigQuery dataset.

• Learn how to confirm billing is enabled for your project
• Learn how to view projects linked to Cloud Billing accounts

If you plan to export your Cloud Billing pricing data to BigQuery, you need to enable the BigQuery Data Transfer Service API. If you don't plan to export your Cloud Billing pricing data, you can skip to Step 4. Create a BigQuery dataset.

The BigQuery Data Transfer Service API should be enabled in the same Google Cloud project you're using to contain your BigQuery datasets. If you followed the recommendation in the project section, this is your FinOps or billing administration Google Cloud project.

To enable the BigQuery Data Transfer Service API, do the following:

1. Sign in to the Google Cloud console and go to the API page.

   Go to the BigQuery Data Transfer Service API page

2. On the top left of the page, select a project. You must enable the BigQuery Data Transfer Service API in the same project you are using to contain your BigQuery dataset. If you followed the recommendation in the project section, this is your FinOps or billing administration Google Cloud project.

3. On the BigQuery Data Transfer Service API page, click Enable to enable the API in your selected project.

For more information on enabling APIs, see the Service Usage documentation.

Before you enable your Cloud Billing data to export to BigQuery, you must create at least one BigQuery dataset to manage your exported data. You can use the same dataset to contain your standard usage cost data, detailed usage cost data, and your pricing data.

A dataset is contained within a Google Cloud project you specify. Datasets are top-level containers that are used to organize and control access to your tables and views. A table or view must belong to a dataset, so you need to create at least one dataset before loading data into BigQuery.

If you use an existing dataset, review the limitations that might impact exporting your billing data to BigQuery, such as being unable to export data to datasets configured to use customer-managed key encryption, or being unable to use a dataset configured with an unsupported region location.

To create a BigQuery dataset, do the following:

1. Sign in to the Google Cloud console and go to the BigQuery page.

   Go to BigQuery page

2. In the project drop-down list ( My Project arrow_drop_down) at the top of the Google Cloud console page, select the project you set up to contain your dataset. Make note of the project ID, as you will use that in the next steps.

3. In the Explorer panel, in the pinned projects section, click arrow_right your-project-ID to expand the project to view any existing datasets and saved queries.

4. Next to the project ID, click the View actions menu (more_vert) and then click Create dataset. The Create dataset panel opens.

   1. Enter a Dataset ID. We recommend an ID that spans projects, such as all_billing_data, rather than a project-specific ID.

   2. Select a Data location. The data location specifies the multi-region or region where your data is stored. All tables within this dataset share this location.

      We recommend selecting a multi-region location (EU or US). For your standard usage cost and detailed usage cost data exports, the location you select can influence whether the previous month's data is added to the dataset retroactively. Review the limitations for more information about dataset locations and data availability.

      Cloud Billing export supports all multi-region locations (EU or US). However, only a subset of dataset region locations are supported for Cloud Billing export to BigQuery. Review the limitations for more information about dataset locations.

      After you create the dataset, the location can't be changed. Learn more about locations.

   3. Ensure that the Enable table expiration option is cleared.

      If you enable table expiration and enter a number of days, any new table created in this dataset is automatically deleted following the specified number of days after creation.

      Caution: If you delete any tables containing exported Cloud Billing data records, those records are gone and we can't backfill the deleted records.

   4. In the Advanced options section, choose an Encryption setting. The default option is Google-owned and Google-managed encryption key.

      If you want to use customer-managed encryption key (CMEK) encryption, select Customer-managed encryption key (CMEK), and choose an encryption key.

      Warning: To use CMEK encryption for your Cloud Billing data, you must enable CMEK at the dataset level. If you enable CMEK encryption at the project or organization level using organization policies, the policy prevents Cloud Billing from writing billing data to the tables in your dataset.

   5. To save, click Create dataset.

See the limitations that might impact exporting your billing data to BigQuery.

If you're a reseller, you can reuse the same project and dataset you just created when you enable the reseller-specific Channel Services billing data export.

You enable Cloud Billing data export in the Cloud Billing section of the Google Cloud console. These are the types of data you can enable to export:

• Standard usage cost data - Contains standard Cloud Billing account cost usage information, such as account ID, invoice date, services, SKUs, projects, labels, locations, cost, usage, credits, adjustments, and currency.

  Use the Standard usage export to analyze broad trends in your cost data.

• Detailed usage cost data - Contains detailed Cloud Billing account cost usage information. Includes everything in the standard usage cost data plus resource-level cost data, like a virtual machine or SSD that generates service usage.

  Use the Detailed export to analyze costs at the resource level, and identify specific resources that might be driving up your costs.

  The detailed export automatically includes resource-level information about Compute Engine. To view a breakdown of Google Kubernetes Engine (GKE) cluster costs in a detailed data export, you must also enable cost allocation for GKE.

• Pricing data - Contains Cloud Billing account pricing information, such as account ID, services, SKUs, products, geographic metadata, pricing units, currency, aggregation, and tiers.

• Committed use discounts (CUD) metadata (Preview) - Contains Cloud Billing CUD metadata information, such as billing account ID, CUD product ID, CUD product type, consumption model ID and description, subscription instance ID, subscription entitlement scope, commitment amount, and term.

To enable your Cloud Billing usage cost or pricing data to be exported to BigQuery, do the following:

1. In the Google Cloud console, go to the Billing export page.

   Go to the Billing export page

2. At the prompt, choose the Cloud Billing account for which you'd like to export billing data. The Billing export page opens for the selected billing account.

3. On the BigQuery export tab, click Edit settings for each type of data you'd like to export. Each type of data is configured separately.

4. From the Projects list, select the project that you set up to contain your BigQuery dataset.

   The project you select is used to store the exported Cloud Billing data in the BigQuery dataset.

   For standard and detailed usage cost data exports, the Cloud Billing data includes usage and cost data for all Google Cloud projects paid for by the same Cloud Billing account.

   For pricing data export, the Cloud Billing data includes only the pricing data specific to the Cloud Billing account that is linked to the selected dataset project.

5. From the Dataset ID field, select the dataset that you set up to contain your exported Cloud Billing data.

   For all types of Cloud Billing data exported to BigQuery, the following applies:

   • The BigQuery API is required to export data to BigQuery. If the project you selected doesn't have the BigQuery API enabled, you're prompted to enable it. Click Enable BigQuery API to enable the API.
   • If the project you selected doesn't contain any BigQuery datasets, you're prompted to create one. If necessary, follow these steps to create a new dataset.
   • If you use an existing dataset, review the limitations that might impact exporting your billing data to BigQuery, such as being unable to export data to datasets configured to use a CMEK, or being unable to use a dataset configured with an unsupported region location.

   For pricing data export, the BigQuery Data Transfer Service API is required to export the data to BigQuery. If the project you selected doesn't have the BigQuery Data Transfer Service API enabled, you're prompted to enable it. If necessary, follow these steps to enable the API.

6. Click Save.

After you enable your Cloud Billing data to be exported to BigQuery, you can change various data export settings, for example:

• Change the location where your exported billing data is stored by editing the export settings.
• Change which types of billing data are exported by disabling or enabling the different types.

Before you update the project or dataset where your billing data is stored, or disable any of your data exports, review the limitations and data availability guidelines for how these updates might impact your billing data exported to BigQuery.

To disable a type of Cloud Billing data being exported to BigQuery, do the following:

1. Select Disable Standard Export, Disable Detailed Export, or Disable Pricing Export accordingly.
2. Select Confirm to save your selection.

To re-enable a disabled export of Cloud Billing data to BigQuery, see Enable your Cloud Billing data to be exported to BigQuery.

To update the project or dataset where your exported billing data is stored, do the following:

1. For the export you want to update, select Edit settings.
2. On the Edit settings page, choose a different project or dataset.
3. Select Save to confirm your updates.

Cloud Billing export to BigQuery uses a service account to manage dataset permissions.

After you enable Cloud Billing export to BigQuery, Google automatically adds a service account as an owner to the dataset that you specify. The service accounts look like this:

• For the Standard and Detailed usage cost datasets: billing-export-bigquery@system.gserviceaccount.com
• For the Pricing dataset: cloud-account-pricing@cloud-account-pricing.iam.gserviceaccount.com

The service accounts are owned and managed by Google and provide the permissions that are necessary for our offline process to create a table and write Cloud Billing records to it.

See the limitations that might impact exporting your billing data to BigQuery.

Shortly after enabling Cloud Billing export to BigQuery, billing data tables are automatically created in the BigQuery dataset. To learn more about these BigQuery tables and the table schemas, see Understanding the auto-created data tables in BigQuery.

• When you first enable the standard or detailed usage cost export to BigQuery, it might take a few hours to start seeing Google Cloud cost data propagate to your BigQuery dataset. Data is exported in chronological order. If your export is configured to include data retroactively for the current and previous month, it might take up to five days for the exported data to fully catch up to your current usage data.
• When you first enable the pricing export to BigQuery, it might take up to 48 hours to start seeing your Google Cloud pricing data.

Learn more about the frequency of the data loads into your BigQuery tables.

Exporting Cloud Billing data to BigQuery is subject to the following limitations.

• The table schema for any of the Cloud Billing data exports can change

  When the table schema changes, such as when new fields are added to a BigQuery table schema for a Cloud Billing data export, any queries that directly reference the exported columns might fail. To resolve this, we recommend creating BigQuery views that query the exported tables and present the information in your preferred structure.

  You can then adjust the queries that feed your reports and dashboards to pull from the views, instead of the exported tables. By using views, you can standardize the structure of the data used in your queries and dashboards.

  The views you create should normalize the data so that all of the relevant tables present the same schema to your queries. This protects you from future schema changes, allowing you to modify the view's underlying query in those instances when the data schema changes.

• BigQuery dataset locations supported for use with Cloud Billing data

  BigQuery datasets are configured to use a location – either a multi-region location (EU or US), or a region location. The dataset location is set at creation time. After a dataset is created, its location can't be changed.

  Cloud Billing data export supports all multi-region locations (EU or US), but only a subset of region locations. When you're configuring your Cloud Billing export settings, if you create or select a dataset that's configured to use an unsupported region location, when you attempt to save your export settings, you'll see an Invalid dataset region error.

  The following table lists the multi-region locations and the region locations that are supported for use with BigQuery datasets that contain Cloud Billing data.

  Americas Asia Pacific Europe

  Multi-region: US

  Regions:

  • northamerica-northeast1 (Montréal)
  • southamerica-east1 (São Paulo)
  • us-central1 (Iowa)
  • us-east1 (South Carolina)
  • us-east4 (Northern Virginia)
  • us-west1 (Oregon)
  • us-west2 (Los Angeles)
  • us-west3 (Salt Lake City)
  • us-west4 (Las Vegas)

  Regions:

  • asia-east1 (Taiwan)
  • asia-east2 (Hong Kong)
  • asia-northeast1 (Tokyo)
  • asia-northeast2 (Osaka)
  • asia-northeast3 (Seoul)
  • asia-south1 (Mumbai)
  • asia-southeast1 (Singapore)
  • asia-southeast2 (Jakarta)
  • australia-southeast1 (Sydney)

  Multi-region: EU

  Regions:

  • europe-central2 (Warsaw)
  • europe-north1 (Finland)
  • europe-west1 (Belgium)
  • europe-west2 (London)
  • europe-west3 (Frankfurt)
  • europe-west4 (Netherlands)
  • europe-west6 (Zurich)

• If you edit your export settings to update the project or dataset where your exported billing data is stored, previously exported billing data isn't backfilled to your new dataset. To include the billing information that was exported prior to the switch, you must manually join the new dataset with the previous dataset. For more information, see Join operation.

• For your BigQuery datasets containing standard usage cost data or detailed usage cost data, the type of location you configure on the dataset impacts the timing of when your Google Cloud billing data is exported to the dataset:

  • If you configure the dataset to use a multi-region location (EU or US), the dataset includes Google Cloud billing data incurred from the start of the previous month from when you first enabled the export. That is, Google Cloud billing data is added retroactively for the current and previous month. For the initial backfill of exported data, it might take up to five days for your retroactive Cloud Billing data to finish exporting before you start seeing your current usage data. This retroactive backfill of data only occurs the first time you enable export. If you edit the export settings to change the project or dataset where your exported billing data is stored, or you are re-enabling the export, then billing data is not added retroactively.

  • If your dataset is configured to use a supported region location, your standard usage cost data and your detailed usage cost data only reflect Google Cloud billing data incurred starting from the date you enabled Cloud Billing export, and after. That is, Google Cloud billing data is not added retroactively for non-multi-region dataset locations, so you won't see Cloud Billing data from before you enable export.

    Note: Cloud Billing data export supports all multi-region locations (EU or US), and a subset of region locations. When you're configuring your Cloud Billing export settings, if you create or select a dataset that's configured to use an unsupported region location, when you attempt to save your export settings, you'll see an Invalid dataset region error.

  • For more details, see Data availability.

• Your BigQuery datasets containing pricing data only collect Google Cloud billing data incurred from the date you set up Cloud Billing export, and after. That is, _Google Cloud pricing data isn't added retroactively, so you won't see Cloud Billing pricing data from before you enable export. For more details, see Data availability.

• When exporting detailed usage cost data, the detailed export automatically includes resource-level information about Compute Engine. To view a breakdown of Google Kubernetes Engine (GKE) cluster costs in a detailed data export, you must also enable cost allocation for GKE.

• Dataset encryption: Customer-managed encryption keys (CMEK) aren't supported when exporting billing data to BigQuery. If you enable CMEK encryption for your billing data dataset, this type of encryption prevents Cloud Billing from writing billing data to the appropriate tables within that dataset. Instead, you need to enable the dataset to use a Google-owned and Google-managed encryption key.

• If you want to use BigQuery row-level security on the table that contains your exported data, you must give the Cloud Billing export service account billing-export-bigquery@system.gserviceaccount.com full access to the table using the BigQuery TRUE filter. The following command grants access to the Cloud Billing service account:

  CREATE ROW ACCESS POLICY cloud_billing_export_policy
  ON `__project_id__.__dataset_id__.__table_id__`
  GRANT TO ('serviceAccount:billing-export-bigquery@system.gserviceaccount.com')
  FILTER USING (TRUE);
  

• Resource-level Tags might take up to an hour to propagate to BigQuery exports. If a tag was added or removed within an hour, or if a resource has existed for less than an hour, it might not appear in the export.

  Resource-level tags are available for the following resources:

  • Compute Engine instances
  • Spanner instances
  • Cloud Run services
  • Artifact Registry repositories

• If you use VPC Service Controls, your BigQuery exports might be blocked. To resolve, you need to manually exempt VPC.

• Understanding the Cloud Billing data tables in BigQuery
• Example queries for Cloud Billing data export to BigQuery
• Visualize spend over time with Looker Studio

• View your Cloud Billing reports and cost trends
• View and download the cost details of your invoice or statement
• View and download prices for Google's cloud services
• Understand your savings with cost breakdown reports
• Analyze the effectiveness of your committed use discounts
• View your cost and payment history

Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License, and code samples are licensed under the Apache 2.0 License. For details, see the Google Developers Site Policies. Java is a registered trademark of Oracle and/or its affiliates.

Last updated 2025-08-07 UTC.

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