Databricks Clean Rooms

Databricks Clean Rooms

Your data is a critical competitive asset, but it often contains sensitive content and PII that must be protected. While external AI and ML platforms increasingly require this data to drive accurate business insights, current data privacy regulations make sharing complex. Databricks Clean Rooms can help.

Our Customers

Supporting teams at

AlightModernaGuardianGileadDatabricksAmazonAvesisAsappPagayaLazard

Safely, securely and legally share your data with trusted partners and external AI engines_

Whether you’re providing data to an outside entity, company or partner as part of a content collaboration effort, or looking to expose internal data to externally hosted AI/ML engines for processing, Clean Rooms provides a cross-platform service capable of ingesting and obfuscating data prior to presentation to any 3rd party. Core source data never leaves its root location and obfuscated data, free of PII, GDPR, HIPAA or alternate sensitive content, stays completely within the owner’s control throughout its utilization.

What

Clean Rooms Key Benefits

Secure Cross-Platform Collaboration

Share and analyze data seamlessly across all major cloud providers as well as Dell ECS on-premise environments while maintaining complete control over sensitive information.

Leverage AI/ML Safely

Utilize advanced AI and Machine Learning tools with confidence, knowing your sensitive data remains protected and within your control.

Unlock Combined Data Value

Safely merge and analyze multiple data sources without exposing or compromising source data, maximizing insights while minimizing risk.

Sequential steps to take in your Databricks Cyber Intelligence journey

Why Rearc?

Rearc is an early Clean Rooms adopter

Having worked with Clean Rooms for an extensive period of time prior to the product reaching public release, Rearc successfully performed the very first public client Clean Rooms installation, allowing for secure data sharing between two separate corporations without either having to provide original or full content to the other. Associated metadata was temporarily cataloged, desired content and reporting was assembled and final outputs delivered independently to each side. It’s important to note that the outputs generated for each participating company were not identical but were specific to each entity's individual use case when utilizing the mutually compiled dataset. This is a common use case for Clean Rooms where alternate content generation goals can be met by alternate entities using a single secure, combined and shared metadata set.

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