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Data Modeling Best Practices

Data Modeling Best Practices

Data Modeling Best Practices

Data Modeling Best Practices

Data Modeling Best Practices

Data Modeling Best Practices

Data Modeling Best Practices

Data Modeling Best Practices

Data Modeling Fundamentals

Data modeling defines and organizes data structures to represent real-world entities and their relationships.

Entity-Relationship Diagrams

ER diagrams map entities (nouns) and relationships (verbs). Key cardinalities: one-to-one, one-to-many, many-to-many.

Customer:

attributes: id, email, name, created_at

relationships: has_many Order

Order:

attributes: id, customer_id, status, total, created_at

relationships: belongs_to Customer, has_many OrderItem

Normalization

Aim for third normal form (3NF) in transactional systems:

• 1NF: Atomic columns, unique rows

• 2NF: Full PK dependency

• 3NF: No transitive dependencies

\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\-- 3NF design

CREATE TABLE customers (id SERIAL PRIMARY KEY, name TEXT);

CREATE TABLE orders (id SERIAL PRIMARY KEY, customer_id INT REFERENCES customers(id));

CREATE TABLE order_items (id SERIAL PRIMARY KEY, order_id INT REFERENCES orders(id), product_id INT, quantity INT);

Denormalization

Denormalize selectively for read performance. Common cases: reporting tables, cached aggregates, distributed databases avoiding joins.

NoSQL Modeling

Model for access patterns first:

// Embed for co-accessed data

{

_id: "...",

customer: { id: "c123", name: "Alice" },

items: [{ product_id: "p1", qty: 2 }]

}

Conclusion

Start with 3NF for data integrity. Denormalize for performance when needed. For NoSQL, design your schema around your query patterns. Document all denormalization decisions with rationale.

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