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Conceptual, Logical, and Physical Data Modeling

A toolarrow-up-right to draw ER diagrams.

More toolsarrow-up-right for data modeling.

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Conceptual Data Model

Start with the business perspective. Focus on identifying the main entities (things your business cares about) and their relationships without worrying about technical details.

Key steps:

  • Interview stakeholders to understand business requirements

  • Identify major entities (Customer, Product, Order, etc.)

  • Define high-level relationships between entities

  • Use simple entity-relationship diagrams with just entity names and relationship lines

  • Validate with business users to ensure you've captured their domain correctly

Example: A retail business might have entities like Customer, Product, Order, and Payment, with relationships showing that customers place orders containing products.

Primary tools:

  • Entity-Relationship Diagrams (ERD) - Simple notation with just entities (rectangles) and relationships (diamonds or lines)

  • UML Class Diagrams - Simplified version showing just class names and associations

  • Crow's Foot Notation - Basic version with just entity boxes and relationship lines

Characteristics at this stage:

  • Very simple diagrams with minimal detail

  • No attributes shown (or just key attributes)

  • Focus on "what" entities exist and how they relate

  • Can be drawn on whiteboards or simple diagramming tools

Tools: Lucidchart, draw.io, Visio, or even PowerPoint

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Logical Data Model

Expand the conceptual model by adding attributes and more detailed relationships while remaining database-agnostic.

Key steps:

  • Add attributes to each entity (Customer has name, email, phone)

  • Define primary keys for each entity

  • Specify cardinality of relationships (one-to-many, many-to-many)

  • Normalize the data to eliminate redundancy (usually to 3rd normal form)

  • Add foreign keys to show how entities connect

  • Define data types conceptually (text, number, date) rather than specific database types

Example: Customer entity gets attributes like CustomerID (primary key), FirstName, LastName, Email, while Order entity gets OrderID, CustomerID (foreign key), OrderDate.

Primary tools:

  • Enhanced ER Diagrams (EER) - Full ERD with all attributes, primary keys, foreign keys

  • Crow's Foot Notation - Complete version showing all attributes and cardinality markers (crow's feet, single lines, circles)

  • IDEF1X - Integration Definition for Information Modeling

  • UML Class Diagrams - With full attributes, keys, and multiplicity notation

  • Barker's Notation - Oracle's notation style

Characteristics at this stage:

  • All entities have complete attribute lists

  • Primary keys marked (often underlined or with PK label)

  • Foreign keys identified (often with FK label)

  • Cardinality shown (1:1, 1:N, M:N)

  • Normalization applied

Tools: ERwin, PowerDesigner, Oracle SQL Developer Data Modeler, MySQL Workbench, ER/Studio

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Physical Data Model

Transform the logical model into a database-specific implementation with all technical details.

Key steps:

  • Choose specific data types for your target database (VARCHAR(50), INT, DATETIME)

  • Add indexes for performance optimization

  • Define constraints (NOT NULL, CHECK constraints, unique constraints)

  • Consider denormalization for performance if needed

  • Add technical columns (created_date, updated_date, version numbers)

  • Design for specific database features (partitioning, compression)

Primary tools:

  • Database-specific ERDs - Same notations as logical but with technical details

  • DDL Scripts (Data Definition Language) - The actual CREATE TABLE statements

  • Database Designer Tools - Built into database platforms

Characteristics at this stage:

  • Specific data types (VARCHAR(100), INT, TIMESTAMP)

  • Indexes defined and shown

  • Constraints detailed (CHECK, DEFAULT, NOT NULL)

  • Triggers, stored procedures noted

  • Physical storage considerations (tablespaces, partitions)

Tools:

  • Database-specific: SQL Server Management Studio, pgAdmin, Oracle SQL Developer

  • Universal: ERwin, PowerDesigner, DbSchema, DBeaver

  • Code-first: Migration scripts in frameworks like Entity Framework, Django ORM, Alembic

Best practices across all levels:

  • Work iteratively - don't try to perfect one level before moving to the next

  • Maintain traceability between levels so changes can flow up and down

  • Use consistent naming conventions throughout

  • Document business rules and assumptions

  • Validate each level with appropriate stakeholders (business users for conceptual, analysts for logical, developers/DBAs for physical)

The key is to let each model serve its purpose: conceptual for communication with business users, logical for analysis and design, and physical for actual implementation.

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