Data Models

Data Model

A structured representation of data,

relationships, meanings, rules, and

constraints

Clear Structure

Organizes entities, attributes, and relationships so the system is understandable.

Less Redundancy

Reduces repeated storage of the same data in multiple places.

Consistency

Keeps one reliable version of data across the system.

Integrity

Defines rules that prevent invalid or incorrect data

Communication

Provides a shared language for users, analysts, and developers.

Better Decisions

Supports accurate reports, analytics, and organizational planning.

Entity

A person, place, object, event, or concept about which data is stored.

Attribute

A property or characteristic of an entity.

Relationship

A connection between entities.

Key

An attribute or set of attributes used to identify records uniquely.

Constraint

A rule that controls valid data.

Conceptual Data Model

Focuses on what data is needed, not how it will

be stored.

Conceptual Data Model

Focuses on what data is needed, not how it will

be stored.

Conceptual Data Model

Uses major entities and relationships.

Conceptual Data Model

Easy for non-technical stakeholders to

understand.

Conceptual Data Model

Often represented with a simple ER diagram.

Logical Data Model

Includes entities, attributes, primary keys,

foreign keys, and constraints.

Logical Data Model

Shows cardinalities and relationship rules.

Logical Data Model

Prepared after conceptual modeling and before

physical design.

Logical Data Model

Helps convert business concepts into

structured database design.

Physical Data Model

Defines table names, column names, data

types, constraints, indexes, and storage

choices.

Physical Data Model

Depends on the selected DBMS, such as MySQL

or SQL Server.

Physical Data Model

Used by database administrators and designers

to create the actual database.

Physical Data Model

Transforms logical structures into executable

database definitions

Hierarchical Data Model

Represents one-to-many relationships clearly.

Hierarchical Data Model

Each child normally has one parent.

Hierarchical Data Model

Data is accessed from top to bottom.

Hierarchical Data Model

Useful for organization charts, file systems,

and categories.

Network Data Model

Can represent many-to-many relationships.

Network Data Model

Useful for connected data.

Entity-Relationship Data Model

Commonly used during conceptual database

design.

Entity-Relationship Data Model

Visualized using Entity-Relationship Diagrams

or ERDs.

Entity-Relationship Data Model

Makes business rules easier to discuss with

users.

Entity-Relationship Data Model

Can later be transformed into relational

tables.

Relational Data Model

Most widely used model for structured business

data.

Relational Data Model

Rows represent records; columns represent

attributes.

Relational Data Model

Tables are connected using primary and foreign

keys.

Relational Data Model

Uses SQL for querying and managing data.

Relational Data Model

Supports integrity and reduction of redundancy.