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Data Modeling

skill-ericwang915-data-scientist-skills-data-modeling · by ericwang915

Create data models: conceptual, logical, and physical models. Entity-relationship diagrams, dimensional modeling (Kimball), Data Vault 2.0, and activity schema patterns. Use when designing databases or data warehouses.

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$ agentstack add skill-ericwang915-data-scientist-skills-data-modeling

✓ scanned · ✓ verified — works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • ✓ Prompt-injection patterns
  • ✓ Secret / credential exfiltration
  • ✓ Dangerous shell & filesystem operations
  • ✓ Untrusted network calls
  • ✓ Known-malicious package signatures

What it can access

  • ✓ Network access No
  • ✓ Filesystem access No
  • ✓ Shell / process execution No
  • ✓ Environment & secrets No
  • ✓ Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

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About

Data Modeling

Purpose

Design data models at conceptual, logical, and physical levels for databases and data warehouses.

How It Works

Modeling Levels

  1. Conceptual: Business entities and relationships (non-technical)
  2. Logical: Detailed attributes, data types, keys, constraints
  3. Physical: Implementation-specific (indexes, partitions, storage)

Methodologies

  • Kimball: Star schema, business-process dimensional modeling
  • Inmon: Enterprise data warehouse, normalized
  • Data Vault 2.0: Hubs, links, satellites — flexible and auditable
  • Activity Schema: Single wide event table pattern

Usage Examples

"Create a dimensional model for our e-commerce analytics"

Output Format

  • Model Diagrams: ERD at each level
  • Data Dictionary: Column descriptions and business rules
  • Implementation SQL: DDL scripts

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.

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