LiveRamp

Prerequisites

• Configure LiveRamp Embedded Identity in BigQuery. For moreinformation, seeEnabling LiveRamp Embedded Identity in BigQuery.
• Coordinate with LiveRamp to enable API credentials for use with EmbeddedIdentity. For more information, seeAuthentication.

Setup

The following steps are required when you use LiveRamp Embedded Identity for thefirst time. After setup is complete, only the input table and metadata tableneed to be modified between runs.

Create an input table

Create a table in the input dataset. Populate the table with RampIDs, targetdomains, and target types. For details and examples, seeInput Table Columns and Descriptions.

Create a metadata table

The metadata table is used to control the execution of LiveRamp EmbeddedIdentity on BigQuery. Create a metadata table in the input dataset.Populate the metadata table with client IDs, execution modes, targetdomains, and target types. For details and examples, seeMetadata Table Columns and Descriptions.

Share tables with LiveRamp

Grant the LiveRamp Google Cloud service account access to view andprocess data in your input dataset. For details and examples, seeShare Tables and Datasets with LiveRamp.

Run an embedded identity job

To run an embedded identity job with LiveRamp in BigQuery, do thefollowing:

1. Confirm that all RampIDs that were encoded in your domain are in your inputtable.
2. Confirm that your metadata table is still accurate before you run the job.
3. ContactLiveRampIdentitySupport@liveramp.comwith a job process request. Include the project ID, dataset ID, and tableID (if applicable) for your input table, metadata table, and outputdataset. For more information, seeNotify LiveRamp to Initiate Transcoding.

Results are generally delivered to your output dataset within three business days.

LiveRamp support

For support issues, contactLiveRamp Identity Support.

LiveRamp billing

LiveRamphandles billing for entity resolution.

TransUnion

Prerequisites

• ContactTransUnion Cloud Supportto execute an agreement to access the service. Provide the details of yourGoogle Cloud project ID, input data types, use case, and data volume.
• TransUnion Cloud Support enables the service for your Google Cloud projectand shares a detailed implementation guide that includes available outputdata.

Setup

The following steps are required when you use TransUnion's TruAudienceIdentity Resolution and Enrichment service in your BigQueryenvironment.

Create an external connection

Create a connection to an external data sourceof theVertex AI remote models, remote functions and BigLake (Cloud Resource)type. You will use this connection to trigger the identity resolution servicehosted in the TransUnion Google Cloud account from yourGoogle Cloud account.

Copy the connection ID and service account ID and share theseidentifiers with the TransUnion customer delivery team.

Create a remote function

Create a remote functionthat interacts with the service orchestrator endpoint that is hosted on theTransUnion Google Cloud project to pass the necessary metadata (including schemamappings) to the TransUnion service. Use the connection ID from the externalconnection that you created and the TransUnion-hosted cloud function endpointshared by the TransUnion customer delivery team.

Create an input table

Create a table in the input dataset. TransUnion supports name, postal address,email, phone, date of birth, IPv4 address, and device IDs as inputs. Followthe formatting guidelines in the implementation guide that TransUnion sharedwith you.

Create a metadata table

Create a metadata table that will store the configuration required by theidentity resolution service to process data, including schema mappings. Fordetails and examples, refer to the implementation guide that TransUnion sharedwith you.

Create a job status table

Create a table that will receive updates about the processing of an inputbatch. You can query this table to trigger other downstream processes in yourpipeline. The possible job statuses are as follows:RUNNING,COMPLETED, orERROR.

Create the service invocation

Use the following procedure to call the TransUnion identity resolution serviceafter collecting all the metadata, packaging it, and passing it to theinvocation cloud function endpoint hosted by TransUnion.

-- create service invocation procedureCREATEORREPLACEPROCEDURE`<project_id>.<dataset_id>.TransUnion_get_identities`(metadata_tableSTRING,config_idSTRING)begindeclaresql_querySTRING;declarejson_resultSTRING;declarebase64_resultSTRING;SETsql_query='''select to_json_string(array_agg(struct(config_id,key,value))) from `'''||metadata_table||'''` where  config_id="'''||config_id||'''" ''';EXECUTEimmediatesql_queryINTOjson_result;SETbase64_result=(SELECTto_base64(CAST(json_resultASbytes)));SELECT`<project_id>.<dataset_id>.remote_call_TransUnion_er`(base64_result);END;

Create the matching output table

Run the following SQL script to create the matching output table. This is thestandard output of the application, which includes match flags, scores,persistent individual IDs, and household IDs.

-- create output tableCREATETABLE`<project_id>.<dataset_id>.TransUnion_identity_output`(batchidSTRING,uniqueidSTRING,ekeySTRING,hhidSTRING,collaborationidSTRING,firstnamematchSTRING,lastnamematchSTRING,addressmatchesSTRING,addresslinkagescoresSTRING,phonematchesSTRING,phonelinkagescoresSTRING,emailmatchesSTRING,emaillinkagescoresSTRING,dobmatchesSTRING,doblinkagescoreSTRING,ipmatchesSTRING,iplinkagescoreSTRING,devicematchesSTRING,devicelinkagescoreSTRING,lastprocessedSTRING);

Configure metadata

Follow the implementation guide that TransUnion shared with you to map yourinput schema to the application schema. This metadata also configures thegeneration of collaboration IDs, which are shareable non-persistentidentifiers that can be used in data clean rooms.

Grant read and write access

Obtain the service account ID of the Apache Spark connectionfrom the TransUnion customer delivery team and grant it read and writeaccess to the dataset containing the input and output tables. We recommendproviding the service account ID with aBigQuery Data Editor roleon the dataset.

Invoke the application

You can invoke the application from within your environment by running thefollowing script.

call`<project_id>.<dataset_id>.TransUnion_get_identities`("<project_id>.<dataset_id>.TransUnion_er_metadata","1");--usingmetadatatable,and1=config_idforthebatchrun

For technical issues, contactTransUnion Cloud Support.

Billing and usage

TransUnion tracks usage of the application and uses it for billing purposes.Active customers can contact their TransUnion delivery representativefor more information.