criteria: • MUST be an AWS customer with UC enabled • MUST have external sharing enabled on the metastore (Delta Sharing) • MUST have a collaborator that they are willing to work with in the clean room private preview. That collaborator must be a Databricks customer (or willing to become one). As an alternate, a customer could also use two metastores for the Private Preview. • MUST be willing to take on egress cost for US-east-2
Clean Rooms customers identity-powered data infrastructure for customer modeling and analytics “LiveRamp and Databricks Clean Rooms give marketers the tools they need to create amazing customer experiences, all while protecting privacy. Databricks customers can harness LiveRamp’s identity-powered data infrastructure to fuel better personalization, stronger collaboration, and greater accuracy for customer modeling and analytics — the dream combination for any marketing team.” – Mike Moreau, VP Operations, LiveRamp Data Sharing + Collaboration Partner
require a great ecosystem Industry & technology partners as well as customers “LiveRamp is a recognized global leader in data collaboration, helping companies build enduring brand and business value by collaborating safely, accurately and efficiently. By integrating Databricks’ advanced analytics technology with LiveRamp’s foundational identity framework — which offers quick access to sophisticated extensive person- and household-based identity graphs — businesses can unlock the full value of their data partnerships and gain a comprehensive understanding of their customers, improve marketing performance, and enrich data for better ML model training and effectiveness.” — Erin Boelkens, VP of Product, Liveramp “Datavant’s mission is to connect the world’s health data for better patient outcomes. Datavant enables healthcare and life science organizations to bring together disparate data sets in a controlled and compliant way. By partnering with Databricks, we natively enable our connectivity tools on the Databricks platform, reducing friction and accelerating time to insight in a privacy-preserving manner.” — Tal Rosenberg, President of Life Science, Ecosystem, and Public Sector, Datavant “As healthcare data lake owners, we would like to be able to apply and adjust privacy rules as needed depending on the data set, but without the exposure to potentially sensitive data. A clean room environment with Databricks allows us to own the processing of sensitive data from data suppliers and apply customized privacy rules in a secured environment without accessing the data directly. It also allows us to spin up a collaborative environment for sensitive data while quickly cutting infrastructure build time from days to minutes.” — Anfisa Kaydak, VP, Data Product and Engineering, HealthVerity
workload from simple joins to AI Streamlined user experience for both power and business users Habu Clean Room powered by Databricks “Habu is the interoperable data clean room solution that unifies insights, activation and measurement across walled gardens, major retailers, media/CTV channels, identity/activation platforms, and other disparate sources. We’re excited to continue our partnership with Databricks, providing the orchestration, no/low-code interface, and privacy-centric automated workflows that make their new data clean room offering more accessible to business users.” —Matt Kilmartin, Co-Founder and CEO, Habu
Databricks Clean Rooms Visit our website → Join our private preview Sign up → <add LP snip when live> Databricks Clean Rooms How are you solving sensitive data use cases today?
Monitoring Tables Files Models Notebooks Dashboards Unified governance for data & AI Users Apps Databricks Unity Catalog Unified visibility into data and AI Simple permission model for data and AI AI-powered monitoring and observability Open data sharing
lock-in with open source Delta Sharing for seamless data sharing across clouds, regions, and platforms, without replication ▪ Share more than just data - Notebooks, ML models dashboards, applications ▪ Explore and monetize data products through an open marketplace ▪ Collaborate securely on sensitive data with scalable data clean rooms Unity Catalog: Open data sharing
Delta Sharing Open cross-platform sharing Share live data with no replication Centralized governance Data Provider Data Consumer Delta Lake table Delta Sharing server Delta Sharing protocol … Any compatible client
than just data - ML models, notebooks, applications and solutions ▪ Evaluate data products faster with prebuilt notebooks and sample data ▪ Avoid vendor lock-in Databricks Marketplace Open marketplace for data, analytics and AI
with Databricks Powered by Delta Sharing: Open, cross-platform data sharing Databricks Marketplace Private Exchange Databricks White Label Databricks Clean Rooms Private Preview on AWS Private Preview on AWS GA on all clouds Allows data providers to make certain data products discoverable only to a specified group of data consumers in the Databricks Marketplace. Compute required: No. Data sharing only. Privacy requirements: Medium. Need to gate who can access data you share on the Marketplace. No limitations to what data consumers can use that data for. You do not want your data available on the public Marketplace. Use case example: A beverage company lists their data products on the marketplace and specifies only that their bottling partners can see and access that data for future analysis. Allows ISVs to offer the full capabilities of the Databricks platform combined with their product/data to create a unique solution to their end customers. Compute required: Yes. Solution needs to execute jobs for customers. Privacy requirements: Med/High. Need to provide an environment that gives specific access to customers regarding what data they can see and what jobs they can run on that data in that environment. Use case example: An analytics solution company provides an insights platform from ingested customer data with Databricks as a backend. Their end customers now have an environment to mix other data sets with those results. Collaborate on data in a secure environment, where multiple parties can safely combine sensitive data without compromising privacy or security. Compute required: Yes. Clean room owner will execute jobs in the clean room. Privacy requirements: High. Parties need an environment that ensures raw data cannot not be exposed to each other and only see outputs after analysis. Need control over what analysis can be done on raw data. Use case example: A media company can securely share their audience data with advertisers in a clean room. It allows them to perform overlap analysis without directly exposing user information they each have collected. Secure data collaboration with Databricks
databricksjapan
tenshoku_draft
kakehashi
linyows
eijikominami
kazzpapa3
stajima
yoshidashingo
salaboy
asei
niwatakeru
moore
jonyablonski
caitiem20
thoeni
jakevdp
paigeccino
sstephenson
3n
chriscoyier
speakerdeck
geeforr
tenderlove
