Jon Chery
43 lines
1.1 KiB
Markdown
43 lines
1.1 KiB
Markdown
# Data — First Principles
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## 1. The Principles
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### P1. Truth
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The schema reflects the domain, not the application. If the data
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model lies, every query lies.
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### P2. Normalization Discipline
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Duplication is a bug waiting to happen. The same fact lives in one
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place.
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### P3. Invariants in the Schema
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Constraints live where the data lives. Application-layer checks are
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defense, not enforcement.
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### P4. Migration Safety
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Schema changes are reversible, non-destructive, and tested. Production
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data is sacred.
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### P5. Indexing with Intent
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Indexes exist for known query patterns. Every index earns its write
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cost.
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### P6. Naming Consistency
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Same concept, same name, always. Across tables, columns, code, and
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APIs.
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### P7. Type Fidelity
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Types match domain meaning. A `string` is rarely the right type for
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an email, an ID, or a status.
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### P8. Lifecycle Awareness
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Data has a creation, a lifetime, and an end. Archival and deletion
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are first-class.
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### P9. Referential Integrity
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Relationships are enforced, not assumed. Foreign keys exist. CASCADE
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is intentional.
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### P10. Performance Awareness
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Schema choices have cost. Query plans are reviewed. Cardinality is
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understood. |