
Data Governance
Data governance is the practice of establishing policies, processes, and responsibilities to ensure the effective and ethical management of an organization’s data assets. It serves as the foundation for trust in data by defining how data is accessed, used, and protected, aligning data practices with business objectives and regulatory requirements.
Policy and Risk Control Models
Governance policies and risk controls are maintained as object models and associated to relevant data assets.
Approval Workflows
Extensible workflows provide a multi-step approval, rejection, and publishing process with defined roles for editors, reviewers, approvers, and publishers.
Federated Governance
MetaKarta's multi-architecture configuration capability supports distributed governance control with standards and oversight of a core team. This is a common requirement of distributed data product ownership approach.
Stewardship Assignment Inheritance
Steward assignments are auto-propogated from terms associated with phyical assets or from a model assignment to all objects within the model.
Change Notification
Stewards are notified when data assets change. This is configurable based on the criticality of the asset.
Policy Monitoring
Worksheet-based analytics monitor policy compliance with aspects such as classification, completeness, standard compliance, and certification validity.
PII Data Classification
Data classification rules and patterns automatically identify PII-related assets, tag them, and assign them to stewards.
Governance Role Configuration
Granular role type permissions at the object model level support any type of centralized or federated role definition and organizational structure, such as council members, data owners, stewards, and data custodians.
Collections & Dashboards
Custom dashboards and domain-specific object collections provide stewards, risk, and data governance leaders with oversight and status.