🏗️ data-architecture

The open-source Claude plugin for data architects.

Community-built skills that turn Claude into a senior data architect — for modeling, platforms, cloud, AI, and modernization.

🚀 Quick Start · 📚 Browse Skills · ✏️ Contribute a Skill · 🗺️ Roadmap

data-architecture is a living, community-built Claude plugin that gives Claude the skills of a senior data architect.

Think of it like brain modules for your AI — each skill you install teaches Claude how to:

• Design data models using Data Vault 2.0, Star Schema, 3NF, and AUDM
• Architect modern platforms: Data Mesh, Data Fabric, Lakehouse, Lambda
• Evaluate and choose cloud technologies: Snowflake, Databricks, Azure Synapse
• Build supply chain analytics from real KPI catalogs
• Design AI/ML feature stores and RAG architectures
• Execute data modernization and migration playbooks

Built at Data Architect School (Accenture, 2024) · 5-day curriculum · community-driven · MIT licensed

# 1. Clone
git clone https://github.com/wjlgatech/data-architecture.git

# 2. Pick a skill and read its instructions
cat skills/day1-modeling/SKILL.md

# 3. Paste into Claude's system prompt or use as a Project instruction

Once installed, Claude responds to built-in commands:

/design-model I need to model a pharmaceutical supply chain with 30 KPIs

/choose-architecture We have 5 source systems, daily batch + real-time events

/kpi-catalog Order Fulfillment domain, OTIF and Perfect Order needed

/audit-vault Review my Hub-Link-Satellite design for DV 2.0 compliance

6 skills · 30 commands · full 5-day curriculum complete. PRs welcome to extend any module.

data-architecture/
├── skills/                       # 🧠 Claude skills (one folder = one skill module)
│   ├── skill-orchestrator/       # Meta-skill: client intake, maturity, engagement orchestration
│   ├── day1-modeling/            # Data modeling: Vault, Star, 3NF, AUDM
│   │   ├── SKILL.md              # Main Claude instructions (paste into system prompt)
│   │   ├── metadata.json         # Skill metadata, version, tags
│   │   ├── commands/             # Slash command definitions
│   │   └── references/           # Deep reference material
│   ├── day2-data-management/     # MDM, Data Quality, Governance, Lifecycle, Security
│   ├── day3-cloud-data/          # Cloud platforms, Lakehouse, FHIR, multi-region
│   ├── day4-analytics/           # Big data, clinical NLP, MLOps, real-time, responsible AI
│   ├── day5-strategy/            # GenAI/RAG, data products, modernization, operating model
│   └── index.json                # Machine-readable skill registry
│
├── knowledge-base/               # 📚 Cross-skill shared domain knowledge
│   ├── healthcare-standards.md   # HL7 FHIR, ICD-10, LOINC, SNOMED
│   ├── cloud-platform-patterns.md
│   ├── analytics-patterns.md
│   └── genai-data-patterns.md
│
├── schemas/                      # 🔒 JSON schemas for CI validation
├── templates/                    # 🧩 Copy-paste starters for new skills
├── examples/                     # 📖 Real case studies (interactive HTML)
│   ├── newlife-pharmacy/         # Pharma supply chain — Day 1
│   └── newlife-hospital/         # Healthcare HIS — Days 2–5
├── docs/                         # 📄 Architecture decisions, specs
├── tests/                        # ✅ Validation scripts (run by CI)
├── scripts/                      # 🛠️ CLI tooling
└── .github/                      # ⚙️ Workflows, issue/PR templates

We merge PRs every day. If your skill passes CI, it gets merged.

# 1. Fork + clone
git clone https://github.com/YOUR_USERNAME/data-architecture.git

# 2. Create a branch
git checkout -b skill/your-skill-name

# 3. Copy the template
cp -r templates/skill-template skills/your-skill-name

# 4. Fill in SKILL.md and metadata.json

# 5. Validate locally
npm run validate

# 6. Open a PR — we'll review and merge same day

→ Full guide: CONTRIBUTING.md

→ Easy wins: good first issue

Paul Wu 🏗️ Founder

Proof of expertise, not slides. Each solution below is a fully-interactive artifact built end-to-end from a real case study. Click to explore.

NewLife Pharmacy — D2P supply chain, 30 KPIs, Data Vault 2.0 vs. Star Schema decision

One-line verdict: Chose Data Vault 2.0 over Star Schema because multi-vendor invoice discrepancies require storing multiple source "truths" simultaneously — something a Star Schema can't do without picking a winner at ETL time.

▶ Open Interactive Solution →

NewLife Hospital — 300 hospitals, 90+ countries, 200M+ patients, HIPAA + GDPR

One-line verdict: Federated Hub-and-Spoke MDM — the only pattern that gives a global patient identity and data residency compliance simultaneously. Pure centralised violates GDPR. Pure decentralised makes "unified" impossible.

▶ Open Interactive Solution →

NewLife Hospital — Multi-region healthcare data platform, FHIR R4 API, Medallion Lakehouse, 90+ countries

One-line verdict: Azure Medallion Lakehouse (Bronze/Silver/Gold) on Delta Lake — the only pattern that handles FHIR R4 streaming ingestion, multi-jurisdictional data residency, and clinical AI feature serving from a single coherent architecture.

▶ Open Interactive Solution →

NewLife Hospital — Clinical NLP, Medical Imaging AI, Real-time Sepsis Alerting, MLOps, $2M→$6M Year-1 ROI

One-line verdict: Lambda architecture for batch + streaming analytics, with a unified MLOps platform (MLflow + Databricks) that governs clinical models from FDA SaMD Class II compliance to bedside alerting in under 60 seconds.

▶ Open Interactive Solution →

NewLife Hospital — RAG pipeline, Data Products, $127M NPV business case, 5-year operating model

One-line verdict: A GenAI Clinical Intelligence Platform built on Retrieval-Augmented Generation, with PHI de-identification gate, vector store serving 200M+ patient records, and a federated data product marketplace — all governed by a CDO-led operating model with a measurable $127M NPV over 5 years.

▶ Open Interactive Solution →

MIT © 2024 wjlgatech and contributors.