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Google BigQuery source
Adobe Experience Platform allows data to be ingested from external sources while providing you with the ability to structure, label, and enhance incoming data using Platform services. You can ingest data from a variety of sources such as Adobe applications, cloud-based storage, databases, and many others.
Read this document for prerequisite steps that you need to complete in order to successfully connect your Google BigQuery account to Experience Platform.
Prerequisites prerequisites
The following section provides further information on prerequisite set up required before you can create a Google BigQuery source connection.
IP address allow list
A list of IP addresses must be added to an allow list prior to working with source connectors. Failing to add your region-specific IP addresses to your allow list may lead to errors or non-performance when using sources. See the IP address allow list page for more information.
Generate your Google BigQuery credentials credentials
To connect Google BigQuery to Experience Platform, you need to generate values for the following credentials:
To authenticate using a combination of OAuth 2.0 and basic authentication, provide the appropriate values for the following credentials.
| table 0-row-2 1-row-2 2-row-2 3-row-2 4-row-2 5-row-2 | |
|---|---|
| Credential | Description |
project |
The project is the base-level organizing entity for your Google Cloud resources, including Google BigQuery. |
clientID |
The client ID is one half of your Google BigQuery OAuth 2.0 credentials. |
clientSecret |
The client secret is the other half of your Google BigQuery OAuth 2.0 credentials. |
refreshToken |
The refresh token allows you to obtain new access tokens for your API. Access tokens have limited lifetimes and can expire during the course of your project. You can use the refresh token to authenticate and request subsequent access tokens for your project when needed. |
largeResultsDataSetId |
(Optional) The pre-created Google BigQuery dataset ID that is required in order to enable support for large result sets. |
For detailed instructions on how to generate OAuth 2.0 credentials for Google APIs, see the following Google OAuth 2.0 authentication guide.
To authenticate using service authentication, provide the appropriate values for the following credentials.
Note: Your service account must have sufficient permissions, such as: BigQuery Job User, BigQuery Data Viewer, BigQuery Read Session User, and BigQuery Data Owner in order to successfully authenticate with service authentication.
| table 0-row-2 1-row-2 2-row-2 3-row-2 | |
|---|---|
| Credential | Description |
projectId |
The ID of the Google BigQuery that you want to query against. |
keyFileContent |
The key file that is used to authenticate the service account. You can retrieve this value from the Google Cloud service accounts dashboard. The key file content is in JSON format. You must encode this in Base64 when authenticating to Experience Platform. |
largeResultsDataSetId |
(Optional) The pre-created Google BigQuery dataset ID that is required in order to enable support for large result sets. |
For more information on using service accounts in Google BigQuery, read the guide on using service accounts in Google BigQuery.
Connect Google BigQuery to Platform
The documentation below provides information on how to connect Google BigQuery to Platform using APIs or the user interface: