Frameworks & Standards
DAMA-DMBOK
DAMA-DMBOK is the DAMA Data Management Body of Knowledge. Buyers use it as a broad data-management lens across governance, architecture, modeling, metadata, quality, integration, lifecycle, security, and operations.
Buyer question
"Does Legra support disciplined data management, or is it only a graph query engine?"
Legra fit
| Data-management area | Legra fit | Status |
|---|---|---|
| Data governance | Workspaces, ownership, membership, validation rules, branch policy, and provenance make governance queryable. | Partial fit |
| Data architecture | Teams can query, share, version, and govern their data within workspaces. | Native fit |
| Metadata management | Metadata can be stored as RDF, versioned, validated, queried, and linked to operational data. | Native fit |
| Data quality | SHACL validation, staging branches, strict production branches, and validation reports support quality controls. | Native fit |
| Data security | Workspace membership, access revocation, encryption, and change history support data security. | Native fit |
| Data operations | Activity monitoring, tasks, events, loading workflows, and branch history support operational visibility. | Partial fit |
What Legra can say
Legra is relevant to DAMA-DMBOK-style assessments because it treats data management artifacts as graph data:
- Policies and validation rules are stored with the data they govern.
- Data models and shapes are queryable, versioned, and branchable.
- Metadata can be queried together with the resources it describes.
- Data quality is enforced before production merge.
- Provenance and events make operational history inspectable.
- Workspace membership lets teams review who can access their data.
Assessment boundary
DAMA-DMBOK covers organizational practice, roles, stewardship, governance process, operating model, and data-management maturity. Legra can support those practices, but it does not replace the organization and process required to run them.
For a DAMA-DMBOK-style program, Legra is best positioned as an data-management tool that makes policy, metadata, quality, lineage, access, and lifecycle evidence queryable.