AWS is planning to update its collaborative data-sharing service, dubbed AWS Clean Rooms, with machine learning capabilities.
The new machine learning capabilities will allow enterprises and their partners to apply machine learning to shared or collective datasets to generate predictive insights without having to share raw data with each other, the company said.
This is achieved by creating lookalike segments of data, which is similar to the original raw dataset.
“With AWS Clean Rooms ML lookalike modeling, you can train your own custom model using your data, and invite your partners to bring a small sample of their records to a collaboration to generate an expanded set of similar records while protecting you and your partner’s underlying data,” Swami Sivasubramanian, vice president of data and AI at AWS, said during his keynote address at AWS re:Invent.
The capability to model lookalike data for healthcare data will be made available in the coming months, Sivasubramanian added.
The machine learning capabilities of AWS Clean Rooms, which in turn is available as a standalone offering and as part of AWS for Advertising and Marketing, will be available in the US East (Ohio), US East (North Virginia), US West (Oregon), Asia Pacific (Seoul), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), Europe (Frankfurt), Europe (Ireland), Europe (London), and Europe (Stockholm) regions.
AWS Clean Rooms, which was released last year at re:Invent, can be accessed via the AWS Management Console, where an enterprise can choose the partner with whom they want to collaborate.
The console provides options to choose data sets to be shared and configure permissions for participants, the company said, adding that the data sets that are being shared in the clean room are encrypted and don’t have to move out of the AWS environment or be loaded into another platform.
Both the enterprises and their partners can run queries on the datasets. It also provides a broad set of configurable data access controls — including query controls, query output restrictions, and query logging — that allow enterprises to customize restrictions on the queries run by each clean room participant, AWS said.
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