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Borderless Data Lakehouse Designer

Guides an agent through designing a multi-cloud open data lakehouse on Google Cloud with an AI serving layer.

Source Download skill
Repository
google/skills
Stars
21,782
Licence
Apache-2.0
Files
6 files

What it does

Once installed, the agent walks you through a structured process for designing a data platform that spans several clouds (Google Cloud, AWS S3, Azure Blob) using Apache Iceberg tables and BigQuery data agents. It asks discovery questions about your data sources, security and workloads, proposes components and Google Cloud products, draws a Mermaid architecture diagram, and writes a solution architecture guide, asking for your confirmation at each stage. The SKILL.md describes implementation and validation phases too, but the portion shown is mainly design.

Great for

  • Architects planning a multi-cloud data lakehouse who want a structured design checklist
  • Data engineers evaluating how Iceberg, BigQuery and Cloud Storage fit together across clouds
  • Teams preparing a design document for review before any infrastructure is built

Skip it if

  • Single-cloud data warehouses, which the skill itself says it should not be used for
  • Work focused on Knowledge Catalog governance or Spark IDE analytics, which points to a different skill; the design is only as current as the Google documentation it fetches and the user's own review

Try asking

  • “Design a borderless open data lakehouse for our S3 and BigQuery data with Iceberg tables and a BigQuery data agent”
  • “Help me discover requirements for a multi-cloud analytics platform connected via Cross-Cloud Interconnect”
  • “Generate a Mermaid architecture diagram separating ingestion and serving subsystems for our lakehouse”
Step-by-step guide: how to use Borderless Data Lakehouse DesignerInstall, first run, examples, tips and FAQs

Install in 3 steps

  1. 1

    Download the skill

    The ZIP contains the 6 original files, the Apache-2.0 licence and an attribution note.

    google-cloud-solution-agentic-ai-borderless-data-lakehouse.zip
  2. 2

    Add it to your agent

    Claude Code (all projects)

    mkdir -p ~/.claude/skills && unzip google-cloud-solution-agentic-ai-borderless-data-lakehouse.zip -d ~/.claude/skills/

    Claude Code / Agent SDK (this project only)

    mkdir -p .claude/skills && unzip google-cloud-solution-agentic-ai-borderless-data-lakehouse.zip -d .claude/skills/

    Claude apps (web/desktop): Settings → Capabilities → Skills → Upload skill, and choose the ZIP.

  3. 3

    Ask for the task

    No special command needed — the agent reads the skill's description and loads it when your request matches. Try one of the prompts above.

Get better results

  • Answer the discovery questions with concrete data source names, volumes and security requirements so the design is specific
  • Review the generated solution-architecture-guide.md against your own cloud contracts and compliance rules before acting on it
  • Check that the agent actually fetched the cited Google Cloud documentation, since the design depends on it

What's inside

  • assets/output-template.md
  • references/attribution.md
  • references/design_recommendations.md
  • references/product_mapping.md
  • references/product_renaming.md
  • SKILL.md

Redistributed unmodified from google/skills under the Apache-2.0 licence. The assessment was drafted with AI from the skill's files on 2026-10-29. Skills can instruct your agent to run code — read SKILL.md and any scripts before installing.