Secure data isn't controlled. It's governed.
DATUM integrates identity, classification, traceability and privacy within the operating model. Security stops being an added layer — it becomes a property of the data.
- GDPR by design
- RBAC + ABAC + dynamic masking
- Immutable audit log and continuous traceability
Controls exist, but data remains exposed.
Four problems we see in organizations with mature analytics platforms — and still: breaches, fines and reactive audits.
Roles unaudited for years, privileges inherited from old reorgs. The internal attack surface grows without measurement.
Without sensitivity labels, all data gets the same level of control: too much or too little. Impossible to apply judgment.
Knowing who accessed what is reconstructed after the incident, not before. Audit is forensic, not operational.
GDPR is met through manual processes and point-in-time reviews, not integrated into the data model.
Security isn't another layer. It's a property of the data model.
Where others add controls on top of the data, DATUM integrates them within the metadata itself.
Compliance stops being extra work and becomes a consequence of design.
The model operates on four indivisible principles.
Remove one and the rest break. That's why DATUM integrates them from the first datum.
Every access responds to a role, a function and a sensitivity level. No default privileges, no silent accumulation.
Each asset has a label — public, internal, confidential, restricted — that determines applicable controls.
Who accesses what, queries, exports and under what justification — recorded in real time, not reconstructed later.
Anonymization, pseudonymization and minimization integrated into the model, not added as an external layer.
What DATUM actually does.
From principles to product. Six capabilities the platform puts into production from day one.
Continuous inventory of roles, groups and privileges synced with the IdP. Detects orphan access and pending reviews.
Classification based on metadata, patterns and data context. No manual tagging required.
Every operation on the data, signed and tamper-proof. Ready for regulatory inspection.
Sensitive data is masked according to role and consumption context, without duplicating tables or breaking queries.
Reversible tokens under key control to allow analytics without exposing real individual identity.
Alerts when personal data appears in zones not classified as sensitive, before it reaches consumption.
Four sensitivity levels, four sets of controls.
Not all data needs the same protection. Classification allows proportional controls — exactly what's needed for the data to flow when it should and stay protected when it must.
We ground the model in sectors where data demands traceability, semantics and operational control.
Not all organisations face the same regulatory, operational or analytical pressure. We adapt our approach to each sector's context and the client's real maturity.
Well-integrated security protects data without blocking business capacity.
What gets unlocked when security stops being a brake and becomes an enabler.
Integrated security removes default access and reduces the internal attack surface.
GDPR requires continuous evidence — not point-in-time inspections. DATUM produces it automatically.
Data can be consumed, shared and used to train AI knowing the control lives in the platform.
A specific profile, a real question.
Demasiados accesos sin revisar, clasificación manual o inexistente y auditorías que requieren reconstruir el linaje a mano. En entornos regulados esto no es un riesgo menor — es un hallazgo de auditoría.
Modelo de seguridad del dato con clasificación activa, control de acceso por roles y trazabilidad de uso para cumplimiento regulatorio bancario.
Security is transversal — it's implemented in every layer of the model.
Security, in context
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Do you know where your data security stands?
A 60-minute session to map your situation against the DATUM framework and evaluate next steps.