data-lake-and-zone-architecture — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited data-lake-and-zone-architecture (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
Use this skill when the storage platform needs structure before pipelines scale into chaos. It helps agents design clear lake zones, dataset boundaries, ownership, lifecycle rules, and publish-safe storage conventions.
Do not use this to justify creating extra layers with no operational purpose.
Clarify:
Typical zones include:
Decide:
Include:
Not every dataset in the lake is ready for shared consumption.
Use references/cloud-data-engineering-architecture-patterns.md when the task is not only zone design, but choosing the overall cloud architecture pattern across lake, warehouse, lakehouse, streaming, and hybrid shapes.
| Rationalization | Reality |
|---|---|
| "We can dump everything into one bucket or container and organize later." | That is how data lakes turn into data swamps. |
| "More zones always means better governance." | Extra layers without distinct purpose add complexity and slow teams down. |
| "If the file exists in the lake, it is available for analytics." | Raw landing data rarely has the quality or contract guarantees needed for shared use. |
~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.