A Framework for Evaluating Privacy-preserving Data Infrastructure for Collaboration


Digital transformation has become an imperative for institutions of every size in every industry. As we exit the pandemic, businesses are beginning to double down on their digital transformation initiatives and think longer term. IDC estimates that by 2023, a direct-to-digital transformation investment will approach $7 trillion. Foundational to business efforts in this area is building a strong first-party data and identity strategy.

A key opportunity for any institution, then, is to facilitate data collaboration in a way that preserves privacy at scale. Business leaders are no longer choosing between data privacy and data utility. Instead, they get both.

In business, this can take countless forms. As one example, a retailer with valuable data assets who is considering setting up a media network to unlock a new revenue stream and provide better intelligence to its suppliers.

Inherent in each of these types of multiparty data collaborations is the need to satisfy a variety of technical and privacy requirements. To do so in a way that reduces complexity is a challenge, but not an impossibility with the right framework against which to evaluate privacy-preserving data infrastructure.

Advanced data infrastructures are built on privacy technology rooted in privacy-enhancing mathematical safeguards and possess tailorable privacy controls. These enable your team to easily configure permissions and audit usage. They also allow data to remain where it is currently stored without being copied or moved, regardless of whether data is on prem or stored across cloud architectures. This greatly reduces time to provision data for usage, in addition to keeping it safe. Lastly, leading-edge solutions support a variety of analytics use cases and tooling, and facilitate access to permissioned data to ensure that analysts can perform their usual tasks and generate accurate, actionable insights.

With additional data regulation undoubtedly in our future, customer intelligence will only become more challenging to come by, increasing the need for enterprises to collaborate with data safely and securely. The business leaders that plan for this future now will be the ones poised to reap greater returns on their current investments.

Hear from LiveRamp’s Head of Privacy Technology Solutions (co-founder and former CEO of DataFleets*), David Gilmore, on how to keep private data safe and make private data useful. Join this panel to learn:
- How data collaboration can drive an institution’s data infrastructure and strategy forward
- How data partnerships manifest in various use cases and specific examples, across industries
- Six key considerations to preserve privacy and uphold performance

*DataFleets acquired by LiveRamp in 2021


Nick Elledge is the head of operations for privacy technology at LiveRamp, where he is responsible for accelerating the development of the company’s privacy-enhancing technologies. His extensive experience bringing privacy-first solutions to market is integral to LiveRamp’s international growth. Prior to LiveRamp, Nick founded DataFleets, a privacy-preserving analytics platform. He previously was vice president and chief investment officer of E.L. Rothschild. Before that, he was a venture capital investor at Andreessen Horowitz, an innovation consultant to the United Nations World Food Programme, and a business analyst at McKinsey & Company.

Nick holds an MBA from Stanford University, a Master’s of Public Administration in international economics from Harvard University, a bachelor of science and bachelor of arts in economics and public policy from Southern Methodist University. He loves international travel, ultimate frisbee, and improv comedy."

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