Assesses, designs, and evolves data architectures through workload analysis, platform and modeling tradeoffs, governance, data products, data mesh, event-driven flows, and migration planning.
Use this skill to assess, design, and evolve data architectures, including data platforms, data products, data mesh adoption, event-driven data flows, governance, modeling, and migration decisions. Load it when teams need workload-grounded tradeoffs, ownership and quality agreements, or a current-to-target data architecture. Do not use it for pipeline or platform operations, implementation details, interface contract semantics, SQL tuning, or statistical modeling; route those to data-engineering, platform-engineering, api-design-and-evolution, postgres, or data-scientist.
evals/evals.json
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README.md
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templates/adr-template.md
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Other
templates/architecture-design-session.md
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Reference
references/anti-patterns.md
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references/architecture-patterns.md
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references/case-studies.md
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references/cloud-platform-comparison.md
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references/compliance-by-framework.md
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references/data-mesh-readiness-and-operating-model.md
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references/discovery-framework.md
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references/event-driven-data-products.md
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references/governance-maturity.md
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references/vendor-evaluation.md
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Script
scripts/governance-assessment.py
Python
SKILL.md
SKILL.md
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