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Platform · Quality

Quality SLOs

Your infrastructure has carried uptime targets for years, and this module brings the same discipline to data quality. It sets quality targets per dataset, covering freshness, completeness, accuracy, and whatever else its consumers depend on, and it tracks them continuously. Attainment is computed from sealed check results, so a breach shows the day it happens and nobody can key the number in.

What you get01 / 03
01

SLOs are defined per dataset across freshness, completeness, validity, and accuracy, agreed between the producer and the consumers who depend on it.

02

Targets scale to materiality, so your top-tier CDEs carry tighter commitments than a sandbox extract, deliberately and on the record.

03

Attainment is derived from sealed check results, never set by hand, so there is no field where a bad month gets edited to green.

04

Breaches are visible the day they occur, each one tied to the specific failed checks behind it rather than discovered at quarter end.

05

Running headroom against each target shows through the period, so a dataset trending toward breach is visible before it gets there.

06

SLO history flows straight into scorecards and evidence packs from the same record, with no re-assembly step.

How it works02 / 03
1

Set

Producers and consumers agree targets per dataset, and the definition goes through the decision door like any other change.

2

Measure

Every relevant check result counts toward attainment automatically as it lands.

3

Derive

Attainment is computed from the sealed results. There is no override and nothing to hand-edit.

4

Surface

Breaches and trends show on the dataset record, the owner's queue, and the scorecards, all from one number.

Questions it answers03 / 03

“What quality did we commit to on this dataset, and are we meeting it right now?”

The SLO definition sits on the dataset record, agreed between the producer and its consumers, and attainment is computed continuously from sealed check results. You see the commitment and the current standing in one place, current as of the latest check.

“Which of my feeds are trending toward a breach before it happens?”

The module tracks running headroom against each target through the period, so a dataset trending toward breach surfaces on the record and the owner's queue before the line is crossed.

“Can someone hand-edit the quality number before it reaches my board pack?”

Nobody can. Attainment is derived from sealed check results with no override and nothing to hand-edit, so the number that reaches your board pack is the number the checks produced.

The next step

Start with proof, not a promise.

There are three ways in, and each one earns the next. You approve the exit criteria before we spend any more of your time or budget.

01

A 60-minute working session

Bring one report that is expensive to prove. We walk the mechanism against it. Nothing is required from your side.

02

A two-week guided sandbox

Your team works hands-on against a synthetic sample bank. It requires zero access to your systems and zero procurement.

03

A six-week proof on your systems

We use read-only metadata across five systems and one priority report, scored against criteria both sides sign first. The decision it produces is yours.