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Announcement | How Stagwell built privacy-safe ID matching on Databricks

Tushar_Parekar
Databricks Employee
Databricks Employee

Stagwell has shared a privacy-safe identity matching pattern on Databricks that helps brands connect fragmented first-party data with an identity graph without sending raw customer records outside their own environment.

Whatโ€™s new

  • Install the app where the data already lives: Databricks Apps let partners deploy secure data and AI applications directly inside a customerโ€™s Databricks workspace instead of requiring a separate environment or data export.
  • Keep data governed inside the customer workspace: Databricks Apps can use the logged-in userโ€™s identity for data access, so Unity Catalog permissions, row filters, and column masks still apply automatically.
  • Use clean rooms for privacy-safe matching: Databricks Clean Rooms provide a secure environment where multiple parties can work together on sensitive data without direct access to each otherโ€™s raw records.
  • Protect the app while simplifying deployment: Marketplace distribution gives data providers a way to package and distribute applications and data products more broadly through an open marketplace for data, analytics, and AI assets.
  • Share outcomes without copying the source data: Databricks sharing capabilities are built around live sharing with centralized governance, which helps partners deliver results while avoiding unnecessary replication.

๐Ÿ‘‰ Read the full post here

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