Datum by Anteodata · How it works

Five layers. One governed flow. No shortcuts.

How the metadata-first principle materialises inside the technical platform. Business never accesses Delta. Data enters through Landing and only reaches the domain after governance, quality and authorisation.

Operational guarantees
100%
End-to-end traceability by design
0
Manual pipelines in production
3
Quality levels: OK / WARN / ERROR
Governance model

Three planes. Each with its own technical responsibility.

The DAMA house: governance defines the rules, the platform runs the data lifecycle, exploitation activates the value. That clear separation lets each plane evolve without breaking the others.

The layers of DATUM

A complete model. Not separate pieces.

DATUM covers the complete data cycle — from strategy to data products — in an integrated, governed and secure-by-design model.

Sources
ERPCRMCoreExternal
Data Strategy
Vision, roadmap and executive sponsors
Strategy · Governance
Data GovernancePillar
Real time
Events · streaming
AI / ML
Models on governed data
◈ Metadata
Metadata
Catalogue, glossary and lineage
The core of Datum. Glossary, dictionaries, lineage and operational metadata in real time.
DataOps
Pipelines, quality and automation
Data Products
Business autonomy and federation
Pillar
Data Architecture
Sources, integration and velocity
Data architecture
Security by design
Least privilege, classification and audit
Consumption
AnalyticsReportingAI / MLAPIs
Metadata
The core of Datum. Glossary, dictionaries, lineage and operational metadata in real time.

Metadata does not document. It governs.

The data journey

Five layers. One ascending flow.

Data enters through Landing and only reaches the business after governance, quality and authorisation. Each layer with its purpose, no shortcuts.

PublicationSnowflake or Databricks SQL · 1 warehouse per domain
Business
BusinessKPIs and data products — defined once
Common DataRDM · MDM · CMD · DPO — single corporate semantics
OperationalExact copy per source · base for reprocessing and audit
LandingTemporary landing · batch and streaming

Publication via Snowflake or Databricks SQL Warehouse — depending on the client environment.

The governed pipeline

Seven steps. Always the same ones.

The pipeline isn't written — it's born from metadata. Each step runs only if the previous one fulfils the contract. Zero manual steps.

01
Metadata definition

Owner · meaning · rules. Before touching any technology.

02
Capture to Landing

DB · files · API · Confluent streaming. Idempotent.

03
Persistence in Operational

Faithful copy. Base for reprocessing and audit.

04
Transformation + Quality

OK flows · WARNING logged · ERROR blocks.

05
Common Data

Corporate semantics. Decoupled from the source.

06
KPIs and data products

One KPI defined once. No parallel logic.

07
Governed publication

Snowflake or Databricks SQL. Each domain sees only its data.

OK flows. WARNING is logged. ERROR blocks.

How DATUM decides what data passes

Three states. Deterministic behaviour.

No grey area. Each record receives one of three labels and the platform always acts the same way. Quality isn't 'supervised' — it's enforced.

OK

Data flows to the next layer without intervention.

!
WARNING

The incident is logged and the owner is notified. Data continues.

ERROR

Data is blocked. Doesn't move forward until the owner resolves.

Keep exploring

Go deeper into each layer

The how materializes into architecture, operating framework and deployment plan.

Who leads this in your organisation?

A specific profile, a real question.

Si lidera tecnología o el dato
CTO·CIO · CDO · Arquitecto de datos
«¿Cómo se opera de verdad el metadata-first sin convertirlo en otra capa de fricción?»

Sabemos que el metadato es la pieza clave: gobierna calidad, linaje, accesos y costes. El problema es que lo que nos venden son catálogos pasivos. Documentamos, sí, pero la operación sigue dependiendo del conocimiento de las personas.

En arquitecturas metadata-first operativas, el tiempo de incorporación de un nuevo dominio se reduce un 60%-70% frente a los modelos basados en documentación pasiva.Eckerson Group — Active Metadata Management 2024
Retail internacional · Multi-país
+60%
ahorro operativo

DataOps gobernado con metadato activo: orquestación determinista, observabilidad continua y cero dependencia de personas clave para entender qué pasó con un dato.

Metadata-firstDataOpsObservabilidad
Ready to talk?

Tell us where you are. Within 48h we'll tell you if we can help.

A direct conversation with the founding team. No pre-sales, no generic decks. We review your situation and honestly tell you whether Datum is the right fit.