- Sources overview
- Available source connectors
- Adobe applications
- Advertising
- Analytics
- Cloud storage
- Amazon Kinesis connector
- Amazon S3 connector
- Apache HDFS connector
- Azure Data Lake Storage Gen2 connector
- Azure Blob connector
- Azure Event Hubs connector
- Azure File Storage connector
- Data Landing Zone
- FTP connector
- Google Cloud Storage connector
- Google PubSub
- Oracle Object Storage
- SFTP connector
- Amazon S3 and Azure Blob connector
- Consent & Preferences
- CRM
- Customer success
- Databases
- Amazon Redshift connector
- Apache Hive on Azure HDInsights connector
- Apache Spark on Azure HDInsights connector
- Azure Data Explorer connector
- Azure Synapse Analytics connector
- Azure Table Storage connector
- Couchbase connector
- Google BigQuery connector
- GreenPlum connector
- HP Vertica connector
- IBM DB2 connector
- MariaDB connector
- Microsoft SQL Server connector
- MySQL connector
- Oracle connector
- Phoenix connector
- PostgreSQL connector
- Snowflake connector
- Teradata Vantage connector
- eCommerce
- Local system
- Marketing automation
- Payments
- Protocols
- Streaming
- API tutorials
- Create a base connection
- Explore data
- Collect data
- On-demand ingestion
- Filter data at the source level
- Monitor dataflows
- Update accounts
- Update dataflows
- Retry failed dataflow runs
- Delete accounts
- Delete dataflows
- Save a dataflow as a draft
- UI tutorials
- Create a source connection
- Configure a dataflow
- Advertising connection dataflow
- Analytics connection dataflow
- Batch cloud storage connection dataflow
- Streaming cloud storage connection dataflow
- Consent & Preferences connection dataflow
- CRM connection dataflow
- Customer success connection dataflow
- Database connection dataflow
- Ecommerce connection dataflow
- Marketing automation connection dataflow
- Payment connection dataflow
- Protocol connection dataflow
- Monitor batch dataflows
- Monitor streaming dataflows
- Update accounts
- Update dataflows
- Delete accounts
- Delete dataflows
- Subscribe to sources alerts
- Self-Serve Sources (Batch SDK)
- Error messages
- Flow run notifications
- IP address allow list
- Frequently asked questions
- API reference
- Platform release notes
Google BigQuery
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.
Experience Platform provides support for ingesting data from a third-party database. Platform can connect to different types of databases such as relational, NoSQL, or data warehouses. Support for database providers include Google BigQuery.
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.
Prerequisites
The following section provides further information on prerequisite set up required before you can create a Google BigQuery source connection.
Generate your Google BigQuery credentials
To connect Google BigQuery to Platform, you need to generate values for the following credentials:
| 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 |
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.
Connect Google BigQuery to Platform
The documentation below provides information on how to connect Google BigQuery to Platform using APIs or the user interface:
Using APIs
- Create a Google BigQuery base connection using the Flow Service API
- Explore data tables using the Flow Service API
- Create a dataflow for a database source using the Flow Service API
Using the UI
- Create a Google BigQuery source connection in the UI
- Create a dataflow for a database source connection in the UI
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