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How to connect DataDoe to BigQuery

DataDoe shares your Amazon data through a private Google Analytics Hub listing. Subscribe to the listing to create a read-only linked dataset in your Google Cloud project. You can then query it with BigQuery, Jupyter notebooks, or an AI assistant.

Create a DataDoe BigQuery integration

  1. In DataDoe, go to Integrations → BigQuery and select Create New Integration.
  2. Enter an integration name and choose Integrated or Raw data.
  3. Under Access Management, add the Google account email addresses that should access the listing. The form starts with your DataDoe account email, which you can change.
  4. Review the billing details, confirm them, and select Create Integration.

DataDoe creates a private listing for the selected dataset and shows its Integration URL in the integrations table. The dataset ending in _integrated or _raw stays in DataDoe's Google Cloud project. Creating the integration does not copy it into your project.

Subscribe in your Google Cloud project

  1. Sign in to Google Cloud Console with a Google account listed under Access Management in the DataDoe integration. Your Google Cloud Console session may use a different account from Gmail or DataDoe.
  2. Open the Integration URL from DataDoe.
  3. Select Subscribe. If prompted, enable the Analytics Hub API in your Google Cloud project.
  4. Select the project where you want to query the data, enter a name for the linked dataset, and choose its region. DataDoe's shared dataset is in us-east4 (Northern Virginia); select that region to keep the linked dataset with the shared data.
  5. Save the subscription, then find the linked dataset under your project in BigQuery.

The linked dataset has the name you chose, not DataDoe's _integrated or _raw dataset name. It is read-only and does not copy the underlying data. A Google Cloud project can contain datasets in different regions, so a project with datasets in the EU can also contain a linked dataset in us-east4.

The subscribing account needs the BigQuery User role (roles/bigquery.user) on the destination project. To query the linked dataset, it also needs BigQuery read access there. Ask your Google Cloud administrator for access if you cannot subscribe or run queries. See Google's guide to viewing and subscribing to listings (opens in a new tab).

Fix common access problems

The listing cannot be found

The listing is private. Check which Google account is active in Google Cloud Console and compare it with the email addresses under Access Management in DataDoe. If you need another account to open the link, add its email address to the integration, save the changes, and reopen the Integration URL while signed in with that account.

No dataset appears in your project

Creating the DataDoe integration does not create a dataset in your Google Cloud project. Open the Integration URL and complete the subscription. Then look for the linked dataset under the project and region you selected. It will not be named with DataDoe's _integrated or _raw suffix unless you gave it that name.

Set up credentials for local tools

MCP Toolbox, Jupyter notebooks, and other local tools need Google Cloud credentials for the account that can query your linked dataset. Enable the BigQuery API (opens in a new tab) in the project you use for queries.

Install the Google Cloud CLI (opens in a new tab), then run:

bash
1gcloud init
2gcloud auth application-default login

Use the Google account that has access to your linked dataset. The second command creates Application Default Credentials that local BigQuery tools can use.

Check the cost

DataDoe displays the charge for your plan and dataset type before you create the integration. On the Base plan, there is no monthly DataDoe integration fee: queries cost 0.2 AI Tokens for Integrated data or 0.5 AI Tokens for Raw data. Other plans charge a monthly integration fee of $49 for Integrated data or $149 for Raw data, rather than AI Tokens per query. Google bills BigQuery usage to your Google Cloud account. See Subscription and pricing.

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