Data Quality Watch
Upstream quality slipping. Flags nulls, dupes, and drift before a decision.
Null rate, duplicate rate or distribution drift on a column crosses its profiled envelope, on a table a live playbook depends on.
Quality incident opened against the table and column; dependent playbooks suppressed; profile envelope updated where the change was legitimate.
Every write is gated on an approver role you name. Nothing runs unattended.
- Profile each column against its own history rather than a global rule, since retail data is legitimately seasonal.
- Separate a genuine upstream change from a business change, because a new store or a new banner looks exactly like corruption.
- Trace the downstream dependency: which cards and playbooks read this column, and what they would get wrong.
- Suppress affected outputs and raise the case to the data owner with the sample rows that failed.
- Close when the column returns inside its envelope and the suppressed outputs are recomputed.
Decisions prevented from running on bad data, and time-to-detect on quality regressions, per quarter.
The case closes on this number, not on the action being taken. A playbook without a close condition is a dashboard.
The rest of IT & Data
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Pick three playbooks from the catalog. We wire them against your system of record for the pilot.
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