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Unify customer and partner data with the new entity resolution framework in BigQuery

March 6, 2024
Samarth Shah

Software Engineer

Zissis Konstas

Product Manager

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Announcing the BigQuery entity resolution framework
In today's data-driven world, fragmented information can paint a blurry picture of your users and customers. Connecting the dots between disparate records to reveal a unified identity is a common challenge. Manual data matching is error-prone, time-consuming, and does not scale.

That's where entity resolution can provide critical value. Whether it's stitching together a customer's purchase history across platforms or identifying fraudulent activity hidden within duplicate accounts, entity resolution unlocks the true potential of your data to give you a unified view of who and what matters most.

Match records without moving or copying data
The BigQuery entity resolution framework allows you to integrate with the identity provider of your choice using standard SQL queries. BigQuery customers can now resolve entities in place without invoking data transfer fees or managing ETL jobs. Identity providers can provide their identity graphs as a service on Google Cloud Marketplace without revealing their matching logic or identity graphs to end users.

The BigQuery entity resolution framework uses remote function calls to match your data in an identity provider's environment. Your data does not need to be copied or moved during this process as shown here:

http://storage.googleapis.com/gweb-cloudblog-publish/images/1_Entity_Resolution_Framework.max-1700x1700.png
  1. The end user grants the identity provider's service account read access to their input dataset and write access to their output dataset.

  2. The user calls the remote function that matches their input data with the provider's identity graph data. Matching parameters are passed to the provider with the remote function.

  3. The provider's service account reads the input dataset and processes it.

  4. The provider's service account writes the entity resolution results to the user's output dataset.

Why use entity resolution?
The BigQuery entity resolution framework benefits a wide range of industries and use cases, including:

  • Marketing: Enhance customer segmentation and targeting by clustering customer profiles across channels.
  • Financial services: Identify fraudulent transactions and customer churn by accurately linking financial records.
  • Retail: Gain a holistic view of customer behavior by deduplicating purchase records across platforms.
  • Healthcare: Improve patient care by unifying medical records from disparate sources.
  • Data sharing: Prepare data for use in BigQuery data clean rooms, which allows organizations to share data in low-trust environments.

Entity resolution pricing
The BigQuery entity resolution framework does not incur additional storage or compute costs beyond any fees charged by the identity provider for use of their service. Identity providers pay no additional costs beyond the storage and compute required to implement and run their entity resolution service. The framework is available in all BigQuery compute models and its use is not restricted by edition.

What our partners say about the BigQuery entity resolution framework
We’ve worked closely with entity resolution providers to design our framework. Here’s what they have to say:

“Entity Resolution on BigQuery is truly a game changer that greatly enhances data connectivity while minimizing data movement. Now Google Cloud clients can access an extensible identity framework that spans data warehouses, clean rooms and AI; and marketers can extend their custom data pipelines with a consistent enterprise identity across LiveRamp’s Data Collaboration Platform services. The result: better customer understanding and measurement, and enriched marketing signals to guide brand success.” - Erin Boelkens, VP of Product, LiveRamp

"TransUnion's identity resolution unifies customer data and improves its hygiene through deduplication, verification, and correction. With Entity Resolution on Google Cloud and TransUnion's integration, data engineering teams can reduce setup and ongoing management tasks while making consumer identity ready for insights, audience building, and activation." - Ryan Engle VP of Identity Solutions, Credit Marketing, and Platform Integrations, TransUnion

Take the next step
If you are an identity provider and want to offer your identity resolution service to Google Cloud customers, you can get started today using the BigQuery entity resolution guide. For additional help, ask your Google Cloud account manager to reach out to the Built with BigQuery team

The Built with BigQuery team helps Independent Software Vendors (ISVs) and data providers build innovative applications with Google Data Cloud. Participating companies can: 

  • Accelerate product design and architecture through access to designated experts who can provide insight into key use cases, architectural patterns, and best practices
  • Amplify success with joint marketing programs to drive awareness, generate demand, and increase adoption
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