A data model should reflect how the product and its users understand their work. Early decisions about organizations, records and ownership affect permissions, analytics and future features.
Name the core entities
Write down the nouns in a real workflow, then describe how they relate. A project may belong to an organization, have members and contain tasks. Ask whether a record can move, be shared or be archived, because those actions influence the model.
Define ownership and access
Decide what a user, team and organization can see or change. Multi-tenant products need consistent boundaries throughout queries, exports, background processing and search. Ambiguous ownership is both a product and a security problem.
- Identify who can create and delete each record.
- Decide what happens when a user leaves a team.
- Define how historical records remain available.
Plan the lifecycle
Records are created, updated, archived and sometimes removed. Define required fields and state transitions using the actual business process. Avoid making every field optional merely because the first UI has not been designed yet.
Check reporting needs early
Consider the questions users will ask later and whether the model can answer them without fragile inference. Keep useful timestamps and stable identifiers. Test the model against several realistic scenarios before committing to implementation details.
Practical next step
Model real ownership and change over time. A clear data model reduces surprises in permissions, reporting and integrations.
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