AWS Clean Rooms helps companies and their partners more easily and securely analyze and collaborate on their collective datasets—all without sharing or copying one another's underlying data. With AWS Clean Rooms, you can create a secure data clean room in minutes and collaborate with any other company to generate unique insights about advertising campaigns, investment decisions, and research and development.
Benefits
Create your own clean room, add participants, and start collaborating in a few steps
AWS Clean Rooms helps customers more quickly and easily deploy their own clean rooms without having to build, manage, and maintain their own solutions. Companies can also use APIs to integrate the functionality of AWS Clean Rooms into their workflows.
Collaborate with any company without sharing or revealing underlying data
AWS Clean Rooms makes it quick and easy to generate insights from multi-party data without having to move or share their raw data. Customers can directly permission their data in AWS and start collaborating with their partners' datasets stored in Snowflake and AWS with zero extract, transform, and load (zero-ETL).
Protect underlying data with a broad set of privacy-enhancing controls for clean rooms
AWS Clean Rooms supports stringent data-handling policies through a broad set of privacy-enhancing capabilities including fine-grained analysis rules, AWS Clean Rooms Differential Privacy, and cryptographic computing. And, you can use query logs to understand and audit how your data is queried.
Link and match customer records, use flexible SQL analysis rules, and train and deploy ML models with your partners
With AWS Clean Rooms, you can match and link customer records from across any application, channel, or data store. You can use SQL, Spark SQL, or Analysis Builder to unlock insights, and you can bring your own ML model and deploy it with your partners without having share your custom model or raw data with them.
How it works
AWS Clean Rooms helps customers and their partners more easily and securely collaborate and analyze their collective datasets—without sharing or copying one another’s underlying data.
The first step shows collaboration members and reads, “All collaboration members can contribute plaintext, hashed, or pre-encrypted data.” This step also includes a row of vertically stacked boxes that represent different collaborators and data sources (from top to bottom): contributor 1, first party data; contributor 2, second party data; contributor 3, third party data; and contributor 4, reporting data.
The second step includes a box that reads, “AWS Clean Rooms, collaborate with your partners without sharing raw data.”
The third step shows a square with four icons that illustrate the benefits of the service, including associate tables to use existing records from Amazon S3, set analysis rules to use built-in, flexible rules to control the type of queries that can be run, set output constraints to manage the segment granularity in query results with row-level output constraints, and perform joint data analysis to join and analyze encrypted or plaintext data to get business insights.
The fourth step includes a box that reads, “Amazon S3, receive results in a designated S3 bucket.”
The fifth step illustrates how you can analyze on AWS. It also includes a row of boxes stacked vertically that read (from top to bottom): Amazon QuickSight, Amazon SageMaker, and Amazon Redshift. Below this stack is an icon that reads, "Use with third parties."
The first step defines Cryptographic Computing for AWS Clean Rooms in a box and reads, “Cryptographically prepare data for processing in AWS Clean Rooms collaborations.” This is broken down into the three main ways you can use Cryptographic Computing: 1/ Pre-encrypt data for use in AWS Clean Rooms, 2/ Decrypt results of AWS Clean Rooms collaborations, 3/ Supports CSV and Parquet data formats.
The second step is composed of two arrows flowing from Cryptographic Computing to AWS Clean Rooms and back. The top arrow has text that reads, “encrypted data,” flowing out of Cryptographic Computing into AWS Clean Rooms. The lower arrow reads, “encrypted results,” coming out of AWS Clean Rooms into Cryptographic Computing.
The third step describes AWS Clean Rooms with text that reads, “Collaborate with your partners without sharing raw data.”
Use cases
Enhance customer insights
Bring together disparate data from across engagement channels and partner datasets to form a 360-degree view of your customers.
Optimize marketing and advertising experiences
Collaborate with advertising and marketing partners to improve campaign planning, activation, and measurement, and offer better, more relevant consumer experiences.
Improve reporting and measurement
Securely analyze sensitive datasets across companies and corporate divisions to better predict market trends, assess risk, and improve reporting.
Accelerate research and development
Collaborate to securely accelerate the development of new products, technologies, and programs that rely on datasets across multiple companies.
