[Ultimate]{class="badge positive"}
Create a Google BigQuery source connection in the UI
Read this tutorial to learn how to connect your Google BigQuery account to ÃÛ¶¹ÊÓƵ Experience Platform using the user interface.
Get started
This tutorial requires a working understanding of the following components of Experience Platform:
-
Experience Data Model (XDM) System: The standardized framework by which Experience Platform organizes customer experience data.
- Basics of schema composition: Learn about the basic building blocks of XDM schemas, including key principles and best practices in schema composition.
- Schema Editor tutorial: Learn how to create custom schemas using the Schema Editor UI.
-
Real-Time Customer Profile: Provides a unified, real-time consumer profile based on aggregated data from multiple sources.
If you already have a valid Google BigQuery connection, you may skip the remainder of this document and proceed to the tutorial on configuring a dataflow.
Gather required credentials
Read the Google BigQuery authentication guide for detailed steps on gathering your required credentials.
Connect your Google BigQuery account
In the Platform UI, select Sources from the left navigation to access the Sources workspace. The Catalog screen displays a variety of sources that you can create an account with. You can select the appropriate category from the catalog on the left-hand side of your screen. Alternatively, you can find the specific source you wish to work with using the search bar.
Under the Databases category, select Google BigQuery and then select Add data.
The Connect to Google Big Query page appears. On this page, you can either use new credentials or existing credentials.
Existing account
To connect an existing account, select the Google BigQuery account you want to connect with, then select Next to proceed.
New account
If you are creating a new account, select New account, and then provide a name and an optional description for your new Google BigQuery account.
To use basic authentication, select Basic Authentication and provide values for your project, client ID, client secret, refresh token, and (optional) large results dataset ID. When finished, select Connect to source and allow for a few moments for the connection to establish.
To use service authentication, select Service Authentication and provide values for your project ID, key file content, and (optional) large results dataset ID. When finished, select Connect to source and allow for a few moments for the connection to establish.
Skip preview of sample data skip-preview-of-sample-data
During the data selection step, you may encounter a timeout when ingesting large tables or files of data. You can skip data preview to circumvent the timeout and still view your schema, albeit without sample data. To skip data preview, enable the Skip previewing sample data toggle.
The rest of the workflow will remain the same. The only caveat is that skipping data preview may prevent calculated and required fields from being auto-validated during the mapping step, and you will then have to manually validate those fields during mapping.
Next steps
By following this tutorial, you have established a connection to your Google BigQuery account. You can now continue on to the next tutorial and configure a dataflow to bring data into Platform.