Conceptual Data Modeling

When to Use This Skill

Use this skill when:

• Conceptual Modeling tasks - Working on identify business entities, relationships, and high-level data structures from requirements and domain knowledge
• Planning or design - Need guidance on Conceptual Modeling approaches
• Best practices - Want to follow established patterns and standards

Overview

Conceptual data modeling identifies the essential business entities and their relationships at a high level, independent of any specific database technology. It bridges business requirements and technical implementation.

Conceptual vs Logical vs Physical

Entity Identification Process

Step 1: Extract Nouns from Requirements

Read requirements and identify candidate entities:

Requirements: "Customers place orders for products. Each order contains
multiple items. Products belong to categories."

Candidate Entities:
- Customer
- Order
- Product
- Item (OrderItem)
- Category

Step 2: Filter Candidates

Eliminate non-entities:

• Attributes (name, date, price)
• Derived concepts (total, count)
• Roles (admin is a User role, not an entity)
• Events (unless storing event history)

Step 3: Identify Relationships

Step 4: Define Cardinality and Participation

Customer ─┤├─○< Order     (One customer has zero or more orders)
Order    ─┤├─┤< OrderItem (One order has one or more items)
Product  >○─┤├─ Category  (One product belongs to one category)

Notation:

• ┤├ = Mandatory (must exist)
• ○ = Optional (may not exist)
• < or > = Many side

Conceptual Model Template

# Conceptual Data Model: [Domain Name]

## 1. Domain Overview
[Brief description of the business domain]

## 2. Entity Catalog

### Entity: [Entity Name]
| Property | Value |
|----------|-------|
| Description | [What this entity represents] |
| Business Owner | [Who owns this data] |
| Lifecycle | [Created → Active → Archived] |
| Volume | [Expected record count] |
| Growth | [Expected growth rate] |

**Key Attributes (Business Identifiers):**
- [Natural key 1]
- [Natural key 2]

**Related Entities:**
- [Entity A] - [relationship description]
- [Entity B] - [relationship description]

## 3. Relationship Matrix

| From | To | Cardinality | Description |
|------|-----|-------------|-------------|
| Customer | Order | 1:N | Customer places orders |
| Order | OrderItem | 1:N | Order contains items |
| Product | OrderItem | 1:N | Product appears in items |
| Category | Product | 1:N | Category contains products |

## 4. Entity Relationship Diagram

```mermaid
erDiagram
    CUSTOMER ||--o{ ORDER : places
    ORDER ||--|{ ORDER_ITEM : contains
    PRODUCT ||--o{ ORDER_ITEM : "appears in"
    CATEGORY ||--|{ PRODUCT : contains

5. Glossary

[Business terms and definitions - ubiquitous language]

Domain-Driven Design Alignment

Bounded Contexts

Group entities by business capability:

┌─────────────────────┐  ┌─────────────────────┐
│   Order Context     │  │  Catalog Context    │
│                     │  │                     │
│  ┌───────────────┐  │  │  ┌───────────────┐  │
│  │    Order      │  │  │  │   Product     │  │
│  │   OrderItem   │  │  │  │   Category    │  │
│  │   Shipping    │  │  │  │   Inventory   │  │
│  └───────────────┘  │  │  └───────────────┘  │
└─────────────────────┘  └─────────────────────┘
         ↕                        ↕
    Customer ID             Product ID
   (shared reference)     (shared reference)

Aggregates

Identify aggregate boundaries:

// Order Aggregate
public class Order // Aggregate Root
{
    public OrderId Id { get; }
    public CustomerId CustomerId { get; }
    public List<OrderItem> Items { get; } // Owned by Order
    public ShippingInfo Shipping { get; } // Value Object

    // OrderItems cannot exist without Order
    // Access OrderItems only through Order
}

Value Objects vs Entities

Mermaid ER Diagram Syntax

erDiagram
    CUSTOMER {
        guid id PK
        string name
        string email UK
    }
    ORDER {
        guid id PK
        guid customer_id FK
        date order_date
        string status
    }
    ORDER_ITEM {
        guid id PK
        guid order_id FK
        guid product_id FK
        int quantity
        decimal price
    }
    PRODUCT {
        guid id PK
        string sku UK
        string name
        decimal price
    }

    CUSTOMER ||--o{ ORDER : places
    ORDER ||--|{ ORDER_ITEM : contains
    PRODUCT ||--o{ ORDER_ITEM : "ordered as"

Common Patterns

Hierarchical Data

Category (self-referencing)
├── Electronics
│   ├── Phones
│   │   ├── Smartphones
│   │   └── Feature Phones
│   └── Computers
└── Clothing

erDiagram
    CATEGORY {
        guid id PK
        guid parent_id FK
        string name
        int level
    }
    CATEGORY ||--o{ CATEGORY : "parent of"

Temporal Data

Track state changes over time:

ProductPrice (temporal)
- product_id
- price
- effective_from
- effective_to (nullable = current)

Polymorphic Associations

Attachment can belong to Order OR Product OR Customer:

Option 1: Separate FKs
attachment.order_id, attachment.product_id, attachment.customer_id

Option 2: Polymorphic
attachment.attachable_type, attachment.attachable_id

Validation Checklist

• All business entities identified
• Relationships have clear cardinality
• Naming follows ubiquitous language
• Aggregate boundaries defined
• No premature physical details
• Stakeholders can understand the model
• Glossary defines all terms

Integration Points

Inputs from:

• Requirements documents → Entity candidates
• Domain experts → Business rules
• event-storming (EA plugin) → Domain events

Outputs to:

• er-modeling skill → Logical model
• schema-design skill → Physical model
• DDD implementation → Aggregate design