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data-modeling

Create conceptual, logical, and physical data models with ERDs and data dictionaries.

24|3|Updated Jan 24, 2026
Search Tags:#database design#data modeling#ERD#data dictionary#normalization#data architecture
One-click install
npx skills add https://github.com/Prorise-cool/prorise-claude-skills --skill data-modeling-prorise-cool
Or copy as Structured Prompt for Agent▼
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Skill: data-modeling
Source: https://github.com/Prorise-cool/prorise-claude-skills/tree/main/.claude/skills/product-specialist/references/domains/business-analysis/data-modeling
Command: npx skills add https://github.com/Prorise-cool/prorise-claude-skills --skill data-modeling-prorise-cool

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill addresses the challenge of organizing and representing complex data structures, ensuring clarity, consistency, and efficient database design.

Core Features & Use Cases

  • Data Modeling: Create conceptual, logical, and physical data models using ERDs and data dictionaries.
  • Documentation: Clearly document data structures, relationships, and attributes for better understanding and implementation.
  • Use Case: When designing a new e-commerce platform, use this skill to define all entities (Customers, Products, Orders), their attributes, and the relationships between them, generating ERDs and a data dictionary for the development team.

Quick Start

Generate a Mermaid ERD for an e-commerce data model including Customer, Order, and Product entities.

Frequently Asked Questions about data-modeling

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I create a data model for a new database design?▼

Create a data model by defining entities, attributes, and relationships to generate conceptual, logical, and physical models, ensuring clear and efficient database design.

What is the difference between conceptual, logical, and physical data models?▼

Conceptual data models outline high-level entities, logical models detail attributes and relationships, and physical models specify actual database structures for implementation and data architecture.

How do I generate an ERD and data dictionary for my database?▼

Generate an ERD and data dictionary by documenting your defined data structures, attributes, and entity relationships, which provides clear implementation guidelines for development teams.

Can I document e-commerce data structures like Customer, Order, and Product entities?▼

Yes, you can document e-commerce data structures by defining Customers, Products, and Orders entities, mapping their attributes and relationships to produce an ERD and data dictionary.

Does database design require normalization for structuring data architecture?▼

Normalization is a core keyword in database design used to organize data structures efficiently, reducing redundancy and ensuring data consistency within your conceptual and logical models.

What is the best way to document entity relationships and attributes for a development team?▼

The best way to document entity relationships and attributes is creating a comprehensive data dictionary and ERD, translating complex data structures into clear implementation blueprints.

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