| name | db-conceptual-modeling |
| description | Conceptual data modeling workflow for domain entities, relationships, and lifecycle boundaries. Use when teams must align on domain meaning before logical/physical schema decisions; do not use for index-only or migration-only tasks. |
DB Conceptual Modeling
Overview
Use this skill to model domain meaning first, so later schema decisions reflect business semantics rather than accidental implementation details.
Scope Boundaries
- Teams disagree on entity meaning or relationship semantics.
- A new domain area is being introduced.
- Existing schema complexity suggests conceptual drift.
Core Judgments
- Entity versus value concept boundaries.
- Cardinality and ownership semantics of relationships.
- Lifecycle states and temporal meaning.
- Bounded-context boundaries and shared concepts.
Practitioner Heuristics
- Model business invariants explicitly before table design.
- Use language from domain experts, not only engineering jargon.
- Treat temporal facts (history, validity windows) as first-class concepts.
- Avoid polymorphic catch-all concepts that hide domain distinctions.
Workflow
- Identify core concepts, actors, and business events.
- Define entity relationships with ownership and lifecycle semantics.
- Capture key invariants and conflict rules.
- Resolve term collisions across bounded contexts.
- Document conceptual assumptions that drive downstream logical design.
Common Failure Modes
- Conceptual model mirrors current tables instead of domain reality.
- Relationship ownership is left implicit, causing write conflicts later.
- State transitions are not modeled, forcing ad hoc status flags.
Failure Conditions
- Stop when core terms remain ambiguous across stakeholders.
- Stop when invariants cannot be expressed at conceptual level.
- Escalate when bounded context boundaries are politically unresolved.
