Unclear field semantics—teams then argue across ownership lines.
Schema first
MySQL Schema Design
Wrong schemas force thicker and thicker app-layer patches. Clarify the boundary before choosing the build path.
Tables, keys and constraints designed from access paths to support evolution.
Measure then change
Slow logs and load tests before index/schema changes.
Rollback-minded changes
Schema changes ship with scripts and rollback thinking.
Capacity planning
Estimate growth before sharding—avoid early complexity.
Design issues
These usually show up before a project starts—or right after a rushed launch.
No constraints—dirty data—it often surfaces only after production impact.
Poor primary-key strategy—iteration and local integration slow down.
No archival thinking—users feel it as inconsistent data or UX.
Use-case-driven modeling
List read/write paths; set entity boundaries; constraints for integrity; reserve for growth without early shards.
Derive entities from core use cases—avoid premature over-normalization or casual wide tables. Ship DDL and naming rules.
- Scope written before coding
- Milestones you can accept
- Handover notes included
Highlights
What this engagement typically covers.
Conceptual/logical model
Included in scope after we confirm stack, constraints and acceptance checks.
DDL scripts
Included in scope after we confirm stack, constraints and acceptance checks.
Constraints & initial indexes
Included in scope after we confirm stack, constraints and acceptance checks.
Naming rules
Included in scope after we confirm stack, constraints and acceptance checks.
What you get
- Model notes
- DDL
- Initial indexes
- Naming rules
- Evolution tips
How we work
-
01
Use-case interview, with written stage outputs.
-
02
Model review, with written stage outputs.
-
03
DDL land, with written stage outputs.
-
04
Align with app, with written stage outputs.
Ready to lock scope?
Share core flows—we'll sketch entities.