Dataalttius

Dataalttius is a coined concept in information governance that describes a layered approach to data access and processing, intended to balance data utility with privacy, security, and regulatory compliance. In this framing, data elements are assigned altitude levels that reflect their sensitivity, provenance, and governance requirements. Lower-altitude data are considered less restricted and more readily usable for analytics, while higher-altitude data require additional approvals, stricter controls, and enhanced monitoring. The altitude metaphor is used to help teams visualize tiered protections without tying decisions to individual data sinks or file boundaries.

The term has appeared mainly in educational, speculative, or vendor-agnostic discussions rather than as a formal standard. It is not widely standardized and should be treated as a heuristic rather than an official protocol. In practice, implementing a dataalttius-like approach typically maps to existing data governance constructs such as data classification schemes, role-based access control (RBAC), attribute-based access control (ABAC), data minimization, data lineage, and comprehensive auditing.

Adoption considerations include ensuring that altitude levels align with legal and contractual requirements, avoiding over-constraint that impedes legitimate analytics, and establishing clear policies for elevation (granting higher access) and elevation revocation. Critics argue that the metaphor may add conceptual overhead if not coupled with concrete policy rules and technical controls. Nevertheless, dataalttius is sometimes used to frame discussions about the balance between data usability and privacy, and to guide policy design in multi-tenant or hybrid environments.

Dataalttius remains a conceptual framework rather than a regulated standard, with no dedicated governing bodies or universal definitions. It is primarily found in theoretical discussions, training materials, and some vendor literature as a way to discuss tiered data governance.