Rework Data quality: what I learned (099)

I used this as a focused experiment, and I wrote it down while it was still fresh.

Why I touched it

I made the same flow easier for next week by removing one hidden step.

I kept everything practical by using a short loop around Data quality.

Implementation notes

I started with a narrow goal: keep the same behavior, reduce one risk, and keep rollback trivial. I moved from vague ideas to explicit rules before touching production paths.

Validation checklist

• Pin dependency versions
• Validate against two environments
• Confirm logs remain parseable
• Schedule a review

Snippet

{
  "checklist": ["scope", "timeouts", "telemetry"],
  "owner": "you"
}

I also ran this while working from a weekend camping test for one IRL pass.

What I kept

• This data quality setup now has a measurable improved mean time to fix path.
• I keep the same format for every future run.
• If it can be explained in one checklist, it usually scales better.