Designing a Basic Data Model
What must remain true about the business record when people edit, archive, export, or restore it? Begin with business facts and rules, then test the model against representative workflows and changes.
What You Will Be Able to Decide
- Explain designing a basic data model in product and business terms.
- Apply this decision: Begin with business facts and rules, then test the model against representative workflows and changes.
- Recognise this material risk: the schema mirrors current forms rather than the durable concepts the business depends on.
- Use this review: Use one CRM contact and its related opportunity to test missing values, duplicate records, deletion, and restore.
A founder is deciding how the product should remember information and preserve its meaning over time. This lesson gives you a concrete question to take into a build brief, proposal review, or product decision.
What must remain true about the business record when people edit, archive, export, or restore it? The course example is A lightweight CRM for a two-person sales team; use it to decide what evidence would justify the choice before a builder implements it.
What Does Designing a Basic Data Model Mean for Your Product?
A founder is deciding how the product should remember information and preserve its meaning over time.
Use the illustrative service for this course (A lightweight CRM for a two-person sales team) to make the choice concrete. What must remain true about the business record when people edit, archive, export, or restore it?
Technical term
Designing a Basic Data Model
A data model names the product's entities, attributes, identities, relationships, constraints, and lifecycle.
How Should a Founder Use Designing a Basic Data Model?
For a lightweight crm for a two-person sales team, ask what would happen if the schema mirrors current forms rather than the durable concepts the business depends on.
For this decision, the useful standard is that the data model can represent the real business rules without ambiguity or silent corruption.
- Decision: Begin with business facts and rules, then test the model against representative workflows and changes.
- Evidence to request: show that the data model can represent the real business rules without ambiguity or silent corruption.
- Owner: name who will respond if the schema mirrors current forms rather than the durable concepts the business depends on.
- Record the result in the data model and recovery plan.
- Practical review: Use one CRM contact and its related opportunity to test missing values, duplicate records, deletion, and restore.
How Do You Choose an Approach to Designing a Basic Data Model?
What must remain true about the business record when people edit, archive, export, or restore it? Begin with business facts and rules, then test the model against representative workflows and changes.
The risk is that the schema mirrors current forms rather than the durable concepts the business depends on. Compare a simpler option with the proposed one, including who will operate either choice.
- Describe the user or business outcome that must be protected.
- Identify the most credible failure and its consequence.
- Compare the simplest adequate approach with one realistic alternative.
- Set a review point for when the decision may need to change.
What Evidence Should You Accept for Designing a Basic Data Model?
What Warning Signs Should You Look For?
- The proposal does not address this risk: the schema mirrors current forms rather than the durable concepts the business depends on.
- Nobody can show whether the data model can represent the real business rules without ambiguity or silent corruption.
- The decision has no named owner or review point.
What Should You Ask a Consultant?
- What changes for the user if we choose this approach to designing a basic data model?
- How have we reduced or accepted this risk: the schema mirrors current forms rather than the durable concepts the business depends on.
- Can you demonstrate that the data model can represent the real business rules without ambiguity or silent corruption?
- Who owns the result, and when will we reconsider it?
Key takeaway
Key Takeaway
Begin with business facts and rules, then test the model against representative workflows and changes. Ask for evidence against the specific risk: the schema mirrors current forms rather than the durable concepts the business depends on.