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Who can work with Qlik AutoML

User access to AutoML resources and functionality is determined by the following controls:

  • User entitlement

  • Assignment of specific security roles

  • Access to the space where the resources are located

See the sections below for details about each requirement.

User entitlement

You must have Professional or Full User entitlement in the tenant to view and work with Qlik AutoML.

AutoML security roles

Tenant administrators and the service account owner can work together to control which users in the tenant can use Qlik AutoML. This control is achieved by assignment of global user roles.

Each role defines specific access controls, depending on the actions the user will typically be performing. The following user roles are available:

  • Automl Experiment Contributor

  • Automl Deployment Contributor

A user with the Automl Experiment Contributor role typically creates and manages ML experiments. They can also view ML deployments and create new deployments from experiments.

A user with the Automl Deployment Contributor role typically works with ML deployments. They can create and manage ML deployments, and configure and run predictions from those deployments. A user with this role can also view ML experiments.

A user can have both roles at the same time. Users without either role cannot view or access AutoML resources.

For more information, see Permissions granted by security roles (user-based subscriptions) or Permissions granted by security roles (capacity-based subscriptions).


Experiments, ML deployments, and prediction datasets are stored in Catalog. Filter by type or use the collections to find them easily.

In addition to the AutoML security roles, permissions for working with AutoML are further governed by the spaces where the resources are located.

In addition to the applicable AutoML security roles, you also need the Private Analytics Content Creator role to generate predictions and store them in your personal space.

To work with AutoML resources in a shared or managed space, you need the applicable AutoML security roles, as well as sufficient permissions in the space. For more information about what is required for each space type, see:

Administering experiments and ML deployments

In the hub, tenant and analytics administrators can perform the following actions without any additional security roles or space permissions:

  • View all experiments and ML deployments in the space

  • Delete experiments and ML deployments (only tenant administrator can delete these assets from another user's personal space)

For other actions, the admin must have the required space role.

Tenant admins can manage experiment and ML deployment jobs from the Management Console. For more information, see Managing experiments and ML deployments.

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