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    Interface DataScienceTeamProps

    Data science team configuration for ML infrastructure deployment. Defines SageMaker Studio domain, S3 mini data lake, Athena workgroup, execution roles, user profiles, and team access controls.

    Use cases: Team ML environment setup, shared data lake access, collaborative notebook development, SageMaker Studio provisioning

    AWS: SageMaker Studio Domain, S3, Athena, IAM

    Validation: Requires dataAdminRoles and teamExecutionRole; studioDomainConfig optional

    interface DataScienceTeamProps {
        dataAdminRoles: MdaaRoleRef[];
        inventories?: { [key: string]: InventoryDefinition };
        studioDomainConfig?: DomainProps;
        teamExecutionRole: MdaaRoleRef;
        teamUserRoles?: MdaaRoleRef[];
        verbatimPolicyNamePrefix?: string;
    }
    Index

    Properties

    dataAdminRoles inventories? studioDomainConfig? teamExecutionRole teamUserRoles? verbatimPolicyNamePrefix?

    Properties

    dataAdminRoles: MdaaRoleRef[]

    Admin roles granted access to team resources including KMS keys, S3 buckets, and SageMaker resources.

    Use cases: Team administration, resource management, infrastructure governance

    AWS: IAM roles for team resource administration

    Validation: Required; MdaaRoleRef[]

    inventories?: { [key: string]: InventoryDefinition }

    S3 inventory configurations for team data lake bucket content analysis and governance.

    Use cases: Data governance, cost analysis, content reporting, bucket management

    AWS: S3 inventory configurations

    Validation: Optional; Map of string keys to InventoryDefinition

    studioDomainConfig?: DomainProps

    SageMaker Studio domain configuration for the team's collaborative ML development environment. Supports IAM and SSO auth modes, VPC config, lifecycle configs, custom images, and notebook sharing.

    Use cases: Collaborative ML development, team Studio environment, shared ML resources

    AWS: SageMaker Studio Domain

    Validation: Optional; DomainProps

    teamExecutionRole: MdaaRoleRef

    Execution role for SageMaker workloads including training jobs, endpoints, and notebooks. Must have sagemaker.amazonaws.com service trust.

    Use cases: SageMaker job execution, model training, notebook execution

    AWS: IAM role with SageMaker service trust

    Validation: Required; MdaaRoleRef; must trust sagemaker.amazonaws.com

    teamUserRoles?: MdaaRoleRef[]

    Team member roles for accessing shared resources like data lake, SageMaker Studio, and collaborative tools.

    Use cases: Team member access, ML development, collaborative workflows

    AWS: IAM roles for team member permissions

    Validation: Optional; MdaaRoleRef[]

    verbatimPolicyNamePrefix?: string

    Custom policy name prefix for portable naming across accounts with SSO integration. When set, uses this prefix instead of the naming module for policy names.

    Use cases: SSO integration, cross-account portability, permission set integration

    AWS: IAM policy naming prefix

    Validation: Optional; String

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