Configure a Google Cloud Storage Data Connection (LiveRamp-Hosted)
If you have data in Google Cloud Storage (GCS) and want to be able to use that data in questions in LiveRamp Clean Room, you can create a Google Cloud Storage data connection.
Note
You can connect GCS to LiveRamp Clean Room from your own GCS account instead of using a LiveRamp-hosted GCS account. For more information, see "Configure a Google Cloud Storage Data Connection (Customer-Hosted)".
A LiveRamp-hosted Google Cloud Storage data connection can be used in the following clean room types:
Hybrid
Confidential Computing
BIgQuery
After you’ve created the data connection and Clean Room has validated the connection by connecting to the data in your cloud account, you will then need to map the fields before the data connection is ready to use. This is where you specify which fields can be queryable across any clean rooms, which fields contain identifiers to be used in matching, and any columns by which you wish to partition the dataset for questions.
After fields have been mapped, you’re ready to provision the resulting dataset to your desired clean rooms. Within each clean room, you’ll be able to set dataset analysis rules, exclude or include columns, filter for specific values, and set permission levels.
To configure a LiveRamp-hosted Google Cloud Storage (GCS) data connection, see the instructions below.
Overall Steps
Perform the following overall steps to configure a LiveRamp-hosted GCS data connection:
For information on performing these steps, see the sections below.
Guidelines
Review the following guidelines before starting the setup process:
LiveRamp Clean Room supports CSV and Parquet files, as well as Delta tables and multi-part files. All files should have a file extension. All CSV files must have a header in the first row. Headers should not have any spaces or special characters and should not exceed 50 characters. An underscore can be used in place of a space.
LiveRamp encourages the use of partition columns for optimal question run performance.
Generate a Google Cloud Storage Database in LiveRamp Clean Room
To generate a GCS database in LiveRamp Clean Room:
From the navigation pane, select Data Management → Data Source Locations.
In the row for LiveRamp-Hosted Google Cloud Storage, click .
Note
These credentials may also be generated when creating a new data connection.
Add the Credentials
To add credentials:
From the LiveRamp Clean Room navigation pane, select Data Management → Credentials.
In the row for the Habu Google Service Account Credential Source, select "Activate" from the Actions menu
Review the credentials information and then click .
The next screen displays the Google Project ID and the Credential JSON.
Copy and store the credentials in a secure location.
Use the credentials to authorize and send files to the LiveRamp-hosted GCS bucket generated in the previous procedure.
Create the Data Connection
After you've added the credentials to LiveRamp Clean Room, create the data connection:
From the LiveRamp Clean Room navigation pane, select Data Management → Data Connections.
From the Data Connections page, click .
From the New Data Connection screen, select "LiveRamp-Hosted Google Cloud Storage".
If you've already generated credentials, they will automatically populate. Otherwise, you can generate or regenerate credentials from this page.
Complete the following fields in the Set up Data Connection section:
To use partitioning on the dataset associated with the data connection, slide the Uses Partitioning toggle to the right.
Category: Enter a category of your choice.
Dataset Type: Select Generic.
File Format: Select CSV, Parquet, or Delta.
Note
All files must have a header in the first row. Headers should not have any spaces or special characters and should not exceed 50 characters. An underscore can be used in place of a space.
If you are uploading a CSV file, avoid double quotes in your data (such as "First Name" or "Country").
Quote Character: If you're uploading CSV files, enter the quote character you'll be using (if any).
Field Delimiter: If you're uploading CSV files, select the delimiter to use (comma, semicolon, pipe, or tab).
Data Location: The Data Location will automatically populate with the GCS bucket location generated in the "Generate a Google Cloud Storage Database in LiveRamp Clean Room" section above.
Identifier Type: You do not need to make a selection for this field.
Sample File Path: If you enabled partitioning above, enter the location of a data schema reference file.
Complete the following tasks and fields in the Data Location and Schema section:
To use partitioning on the dataset associated with the data connection, slide the Uses Partitioning toggle to the right.
Note
If the data connection uses partitioning, the dataset can be divided into subsets so that data processing occurs only on relevant data during question runs, which results in faster processing times. When using partitioning, a data schema reference file is required to be entered below.
Data Location: The Data Location will automatically populate with the GCS bucket location generated in the "Generate a Google Cloud Storage Database in LiveRamp Clean Room" section above.
Sample File Path: If you enabled partitioning above, enter the location of a data schema reference file.
Note
The data schema reference file name must start with "gs://" and end with a valid file extension (such as ".csv").
The data schema reference file must be hosted in a static location and must have been uploaded within the last seven days.
Review the data connection details and click .
Note
All configured data connections can be seen on the Data Connections page.
If you haven't already, upload your data files to your specified location.
When a connection is initially configured, it will show "Verifying Access" as the configuration status. Once the connection is confirmed and the status has changed to "Mapping Required", map the table's fields.
You will receive file processing notifications via email.
Map the Fields
Once the above steps have been performed in Google Cloud Platform, perform the overall steps in the sections below in LiveRamp Clean Room.
Note
Before mapping the fields, we recommend confirming any expectations your partners might have for field types for any specific fields that will be used in questions.
From the row for the newly created data connection, click the More Options menu (the three dots) and then click .
The Map Fields screen opens, and the file column names auto-populate.
For any columns that you do not want to be queryable, slide the Include toggle to the left.
Note
Ignore the field delimiter fields because this was defined in a previous step.
Click .
The Add Metadata screen opens.
For any column that contains PII data, slide the PII toggle to the right.
Select the data type for each column.
For columns that you want to partition, slide the Allow Partitions toggle to the right.
If a column contains PII, slide the User Identifiers toggle to the right and then select the user identifier that defines the PII data.
Click .
Your data connection configuration is now complete and the status changes to "Completed".
You can now provision the resulting dataset to your desired Hybrid, Confidential Computing, or BigQuery clean room.