Glossary

Data model

The structuring of business concepts into entities, attributes, relationships, domains, keys and referential integrity.

The structuring of business concepts into entities, attributes, relationships, domains, keys and referential integrity. It does not replace the ontological model: it implements it, and it must evolve by design, never by direct database modification.

It comes after the ontological model, not before. Structuring data without having agreed what the concepts mean produces a technically impeccable model that each department interprets its own way.

Related terms

Business entity

An object, actor, event or transaction the organization needs to know about, manage or evaluate, such as Customer, Request, Contract or Payment.

Data architecture

The definition of the data types and sources needed to support the business, expressed in a way stakeholders can understand.

Data lineage

The trail revealing where a data item came from, which process captured or transformed it, which rule modified it, which system received it and which indicator used it.

ETL

The mechanism that extracts, transforms and loads data between systems, integrating them into workflows.

Ontological model

The formal vocabulary of the business: the actors, objects, events, transactions and outcomes the organization handles, and how they relate.

Referential integrity

The condition ensuring relationships between entities remain valid and free of broken references.

Related Data

The mechanism connecting the data model to process execution, associating with each activity the tables it captures or queries, with state-based mandatory fields, scope filters and in-place…