Data Modelling

Top-level UI section for data-modelling artefacts — Query Examples and Relationships / ERDs.

The Data Modelling section of ODD Platform is the home for operator-curated artefacts that describe how data is intended to be used: canonical query examples and the entity-to-entity relationships that collectors extract or that operators define explicitly. The section is intentionally narrow — two child surfaces today — but the role is durable: anything that documents the contract of a dataset (how it's queried, how it's connected) belongs here rather than in the per-entity catalog page.

Open it from the top-level navigation Data Modelling. The route opens on Query Examples by default; a vertical-tabs sidebar switches between Query Examples and Relationships in one click.

Subsections

• Query Examples — operator-curated SQL / KQL / Spark snippets attached to data entities and terms. Surfaces "how the team uses this dataset" as a first-class catalog object instead of leaving it buried in a wiki, with a dedicated faceted search and term-linking workflow.

• Relationships — entity-to-entity links rendered as ERD diagrams. Covers two relationship classes: ENTITY_RELATIONSHIP (foreign-key-style ERD edges between table-class entities) and GRAPH_RELATIONSHIP (free-form graph edges, e.g. between Neo4j nodes).

UI entry points

Path	What
/data-modelling	Redirects to /data-modelling/query-examples.
/data-modelling/query-examples	Query Examples list + creation surface. RBAC-gated by QUERY_EXAMPLE_CREATE.
/data-modelling/query-examples/{id}	Query Example details / edit. RBAC-gated by QUERY_EXAMPLE_UPDATE + QUERY_EXAMPLE_DELETE.
/data-modelling/relationships	Relationships list — ERD and graph relationships discovered across all data sources.

Why this is a separate pillar

For how Data Modelling relates to the other governance pillars (Data Discovery, Master Data Management, Data Lineage, Data Glossary, Data Quality), see Main Concepts → Data Governance map → Pillar differentiation — the canonical home for the six-pillar framing. Data Modelling is its own pillar because it captures the contract of a dataset (how it's queried, how it's connected) — the dataset itself comes from outside; this pillar records the intent and structure layered on top.

Where to next

• If you're documenting how a dataset is queried, start with Query Examples.

• If you're discovering how datasets are connected (foreign keys, cross-schema joins, graph references), start with Relationships.

• For the broader catalog vocabulary (Data Entity, Plugin, Push adapter, …), see Main Concepts.