What problem does it solve?
Data-modeling fundamentals helps you choose and justify a data model by using the formal theory beneath database design, including Codd’s relational model, relational algebra, functional dependencies, and the normal forms.
Core Features & Use Cases
- Normalization theory and anomaly elimination: Explains 1NF through 5NF/BCNF as a sequence of specific constraint-driven fixes rather than vague “best practices.”
- Functional dependencies & key reasoning: Supports reasoning with functional dependency closure and candidate key identification to make normalization claims defensible.
- Relational vs higher-level modeling tradeoffs: Frames Chen’s ER model as an abstraction layer above relations and evaluates denormalization and alternative models (document, graph, event-sourced) at the conceptual level.
- Scope guardrails: Clearly avoids practical persistence/schema implementation work (use data-modeling), migration mechanics (use schema-evolution), indexing decisions (use indexing-strategy), and business-concept discovery (use conceptual-modeling).
Quick Start
Ask: "Given this schema and its functional dependencies, which normal form does it violate, what anomalies could occur, and what theory-based step would fix it?"
