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A backend engineer renames one column that looked unused, nobody on the analytics side hears about it in advance, and by morning a revenue report is quietly wrong.
What you'll have at the end
A written agreement naming a table's schema, freshness promise, and owner, checked automatically before a breaking change ships
You need
One table in your warehouse you can query directly, plus write access to whatever pull request pipeline runs before that table's own pipeline code ships.
Not covered
Choosing between a free and a paid platform to run contracts like this at scale, or writing one for every table in the warehouse at once; this is one table, drafted and enforced end to end.
Leans on
Document what a column means
go there first if this table has several disputed columns beyond the one this recipe glosses in passing.
Open source or paid: choose your team's first data observability tool
reach for this once one contract like this is working and the real question becomes which platform runs dozens of them.
Warn or block: sort your data checks by real risk
use this once this contract's own check is live and other checks need the same required-versus-warning decision.
Checked 26 Aug 2026
Part of the Data Observability cookbook