Creating a collaboration for ML modeling
In this procedure, you as the collaboration creator perform the following tasks:
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Invite one or more members to the collaboration.
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Assign abilities to members, such as the
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Member who can receive output from trained models
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Member who can output from model inference
If the collaboration creator is also the member who can receive results, they specify the results destination and format. They also provide a service role Amazon Resource Name (ARN) to write the results to the results destination.
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Configure which member is responsible for paying for compute costs, model training, and model inference costs in the collaboration.
Before you begin, make sure that you have completed the following prerequisites:
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You have the name and AWS account ID for each member that you want to invite to the collaboration.
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You have permission to share the name and AWS account ID for each member with all members of the collaboration.
Note
You can’t add more members after you create the collaboration.
For information about how to create a collaboration using the AWS SDKs, see the AWS Clean Rooms API Reference.
To create a collaboration for ML modeling
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Sign in to the AWS Management Console and open the AWS Clean Rooms console
with the AWS account that will function as the collaboration creator. -
In the left navigation pane, choose Collaborations.
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In the upper right corner, choose Create collaboration.
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For Step 1: Define collaboration, do the following:
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For Details, enter the Name and Description of the collaboration.
This information will be visible to collaboration members who are invited to participate in the collaboration. The Name and Description helps them understand what the collaboration is in reference to.
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For Members:
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For Member 1: You, enter your Member display name as you want it to appear for the collaboration.
Note
Your AWS account ID is included automatically for Member AWS account ID.
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For Member 2, enter the Member display name and Member AWS account ID for the member that you want to invite to the collaboration.
The Member display name and Member AWS account ID will be visible to everyone invited to the collaboration. After you enter and save the values for these fields, you can't edit them.
Note
You must inform the collaboration member that their Member AWS account ID and Member display name will be visible to all invited and active collaborators in the collaboration.
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If you want to add another member, choose Add another member. Then enter the Member display name and Member AWS account ID for each member who can contribute data that you want to invite to the collaboration.
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If you want to enable Analysis logging, select the Enable analysis logging checkbox, and then under Supported log types, choose Logs from queries.
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Under Allowed query results regions, select one or more AWS Regions where you want to send query results.
By default, only the current Region (such as N. Virginia us-east-1) is selected.
Important
When you enable cross-Region query results delivery, your results may be processed and stored outside the source Region.
For more information about Regions, see Regions and Endpoints in the AWS General Reference.
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(Optional) Manage access to your data with Automatic change request approval by configuring which settings can be changed automatically without manual approvals for a change request. By default, some settings can only be changed by submitting a change request which must be approved by all members before it can take effect.
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Grant member abilities – Choose the abilities that can be granted to collaboration members without manual approval. Members can always contribute data.
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Choose abilities:
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Contribute data (always enabled)
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Receive results
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Auto-approve new members with these abilities – If allowed, any members added with the abilities selected above will instantly join the collaboration. Members added with other abilities will still require manual approval to join.
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Abilities that can be automatically revoked - Choose the abilities that can be revoked without manual approval. Members can always contribute data.
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Choose abilities:
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Contribute data (always enabled)
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Receive results
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If you choose this option, you can track all collaboration configuration modifications through the Change requests history, located on the Details tab of the collaboration details page.
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(Optional) If you want to enable the Cryptographic computing capability, select the Enable cryptographic computing checkbox.
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Choose the following Cryptographic coverage parameters:
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Allow plaintext columns
Choose No if you require fully encrypted tables.
Choose Yes if you want cleartext columns allowed in the encrypted table.
To run SUM or AVG on certain columns, the columns must be in cleartext.
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Preserve NULL values
Choose No if you don't want to preserve NULL values. NULL values won't appear as NULL in an encrypted table.
Choose Yes if you want to preserve NULL values. NULL values will appear as NULL in an encrypted table.
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Choose the following Fingerprinting parameters:
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Allow duplicates
Choose No if you don't want duplicate entries allowed in a fingerprint column.
Choose Yes if you want duplicate entries allowed in a fingerprint column.
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Allow JOIN of columns with different names
Choose No if you don't want to join fingerprint columns with different names.
Choose Yes if you want to join fingerprint columns with different names.
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For more information about Cryptographic computing parameters, see Cryptographic computing parameters.
For more information about how to encrypt your data for use in AWS Clean Rooms, see Preparing encrypted data tables with Cryptographic Computing for Clean Rooms.
Note
Verify these configurations carefully before completing the next step. After you create the collaboration, you can only edit the collaboration name, description, and whether the logs are stored in Amazon CloudWatch Logs.
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If you want to enable Tags for the collaboration resource, choose Add new tag and then enter the Key and Value pair.
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Choose Next.
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For Step 2: Specify member abilities,
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For Analysis using queries and jobs, under the Supported analysis types, leave the Queries checkbox selected.
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For Run queries, choose the member who will initiate the model training
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For Receive results from analyses, choose one or more members who will receive the query results.
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For ML modeling using purpose-built workflows,
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For Receive output from trained models, choose the member who will receive trained model results, including model artifacts and metrics.
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For Receive output from model inference, choose the member who will receive the model inference results.
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View the member abilities under ID resolution using AWS Entity Resolution.
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For Step 3: Configure payment,
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Under Analysis using queries, for Pay for queries, do one of the following actions:
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To have the same member pay for and run queries, select the same member you chose for Run queries.
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To have a different member pay for query costs, select your member account.
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For ML modeling using purpose-built workflows,
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Choose the member who will Pay for model training.
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Choose the member who will Pay for inference job.
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For Pay for lookalike modeling, no action is needed. The Creator of the configured lookalike model is the member who will pay for lookalike modeling.
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(Optional) Choose the member who will Pay for Synthetic data generation.
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For ID resolution with AWS Entity Resolution, no action is needed. The Creator of the ID mapping table is the member who will Pay for ID mapping table.
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Choose Next.
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For Step 4: Configure membership, under Collaboration membership, choose one of the following options:
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For Step 5: Review and create, do the following:
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Review the selections that you made for the previous steps and edit if necessary.
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Choose one of the options.
If you have chosen to ... Then choose ... Create a membership with the collaboration (Yes, join by creating membership now) Create collaboration and membership Create the collaboration, and not to create a membership at this time (No, I will create a membership later) Create collaboration
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