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data-architecture-skill

Design scalable data architectures with data flow, caching, and migration validation.

Updated Mar 2, 2026
Search Tags:#publishing#caching#analytics#migration#etl#data-flow#data-architecture
One-click install
npx skills add https://github.com/dacy/architect-skill --skill data-architecture-skill
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: data-architecture-skill
Source: https://github.com/dacy/architect-skill/tree/main/.claude/skills/data-architecture-skill
Command: npx skills add https://github.com/dacy/architect-skill --skill data-architecture-skill

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill helps data architects design scalable, standards-aligned data systems by coordinating data flow, caching, analytics integration, publishing, and migration patterns across domains.

Core Features & Use Cases

  • Define end-to-end data movement and governance across data stores and pipelines.
  • Align with data standards for consumption, caching, and platform integration.
  • Provide publishing and migration patterns with validation gates.

Quick Start

Outline a scalable data architecture for a new data lakehouse that follows company data standards and includes data flow, caching, and publishing patterns.

Frequently Asked Questions about data-architecture-skill

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

FAQPage Schema
How do I design scalable data architecture for an enterprise data lakehouse?▼

Design scalable data architecture by mapping end-to-end data flow across stores, defining caching TTL and invalidation rules, and establishing publishing schemas that enforce enterprise data standards.

What's the best way to plan a data migration with rollback validation?▼

Plan a data migration by enforcing validation gates at each pipeline stage and establishing a rollback plan, ensuring data integrity is verified before finalizing the migration across enterprise systems.

How do I structure caching strategies for analytics platform integration?▼

Structure caching strategies for analytics integration by defining specific TTL values and invalidation triggers, ensuring data consumption aligns with governance standards and prevents stale analytics.

When do I need formal data flow mapping for ETL pipelines?▼

You need formal data flow mapping for ETL pipelines when coordinating data movement across multiple domains, enforcing standards for consumption, publishing schemas, and platform integration.

Does this data architecture approach work for high-volume publishing pipelines?▼

This approach supports high-volume publishing pipelines by enforcing defined publishing schemas and data flow governance, ensuring scalable data consumption and standards alignment across enterprise domains.

Why does my data migration fail validation gates without rollback planning?▼

Data migration validation fails without rollback planning because there is no recovery mechanism for integrity errors; enforcing validation gates with rollback ensures safe migration across enterprise systems.

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