Configure an Amazon Web Services Data Connection (LiveRamp-Hosted)
How to configure an Amazon Web Services (AWS) data connection that is hosted by LiveRamp within Clean Room, including steps for setting up the connection, configuring permissions, and verifying the integration.
LiveRamp Clean Room’s application layer enables companies to securely connect distributed datasets with full control and flexibility while protecting the privacy of consumers and the rights of data owners.
To configure a LiveRamp-hosted Amazon Web Services (AWS) data connection, see the instructions below.
Note
You can connect AWS to LiveRamp Clean Room using your own AWS S3 bucket instead of using a LiveRamp-hosted one. For more information, see "Configure an Amazon Web Services Data Connection (Customer-Hosted)".
Overall Steps
Perform the following steps to configure a LiveRamp-hosted AWS data connection in LiveRamp Clean Room:
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 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.
The folder where the data files are dropped can optionally include a date macro. The path in the data-in configuration should be like the following with the date macro abc/xyx/{yyyy-MM-dd} and the actual data files should be under the appropriate date folder. The date macros can appear anywhere in the path. The date must be within seven days of job creation.
LiveRamp encourages the use of partition columns for optimal question run performance.
Generate an AWS Data Source Location in LiveRamp Clean Room
From the navigation pane, select → .
In the row for Habu AWS S3, click .
Add the Credentials
To add credentials:
From the LiveRamp Clean Room navigation pane, select Data Management → Credentials.
In the row for the HABU_AWS credential source, select "Activate" from the Actions dropdown.
Click .
Review the credentials information and then click .
The next screen will display the following parameters:
AWS Access Key ID
AWS Secret Access Key
User ARN
Copy and store the credentials in a secure location for the next procedure.
Use the credentials to authorize and send files to the LiveRamp-hosted AWS S3 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 "Habu AWS S3".
If you've already generated credentials, they will automatically populate. Otherwise, you can generate or regenerate credentials from this page.
Configure the data connection:
Name: Enter a name of your choice.
Category: Enter a category of your choice.
Dataset Type: Select Generic.
Sample File Path: A sample file to use for inferring the schema and understanding how partition columns will be leveraged in questions (for use if defining partition columns). For example, "s3://habu-client-org-123ab456-7d89-10e1-a234-567b891c0123/purchase_events/brand-id=1234/file.csv".
Data Location: The data location will automatically populate with the AWS S3 bucket generated in the first procedure. The macro will be replaced by the true date of the upload. For example, "gs://habu-client-org-123ab456/uploads/HABU_AWS/purchase_events/{yyyy-MM-dd}/full".
File Format: Select CSV.
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").
Field Delimiter: If you are uploading CSV files, select the delimiter to use (comma, semicolon, pipe, or tab).
Review the data connection details and click .
Upload your data files to your specified location.
All configured data connections can be seen on the Data Connections page.
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 connection is confirmed and the status has changed to "Mapping Required", map the table's fields and add metadata:
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.
If needed, update any column labels.
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".