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Dataset Quality Statuses (SLA)

Operator-set Minor / Major / Critical severities on dataset test results, the dataset-level aggregate SLA colour, and the /sla (PNG) and /sla_report (JSON) endpoints for BI import.

Mark the importance of each test on a dataset using Minor, Major, and Critical severities. The platform aggregates those severities together with the test pass / fail counts into a single dataset-level SLA colour (Green / Yellow / Red) that downstream BI reports can import directly.

Setting severities

Severities are operator-set — the platform does not infer them.

  1. Open the dataset's main page and select the Test reports tab.

  2. Click on a job (a test result row) and, in the right-side panel, choose a severity — Minor, Major, or Critical — then confirm the change in the dialog that appears. The severity is only saved once you confirm; the panel always shows the test's stored severity until then.

Severities apply per-test, not per-dataset; one dataset can carry tests at all three severities. Each test's severity together with whether the latest run passed feeds the dataset's aggregate SLA colour.

Importing SLA into BI reports

Each dataset exposes its current aggregate SLA through two endpoints — one returns a pre-rendered PNG badge, the other returns the structured JSON report. Use whichever fits your BI tool's integration model.

Endpoint

Content-Type

Use for

GET /api/datasets/{data_entity_id}/sla

image/png

A pre-rendered PNG badge (1–2 KB). Suitable for BI tools that can embed an image URL directly (Confluence macros, Notion image embeds, Excel IMAGE() formula, Looker / Tableau image tiles).

GET /api/datasets/{data_entity_id}/sla_report

application/json

The structured DataSetSLAReport — current SLA colour (GREEN / YELLOW / RED), severity-weights breakdown, and a sla_ref self-link. Use this when your BI tool parses JSON (BI dashboards that compute their own visualisation, custom report pipelines, internal-tools dashboards).

In both cases {data_entity_id} is the numeric ID of the dataset's data entity — the same ID that appears in the dataset's catalog URL.

Choosing between the two: if your destination renders an image natively, the /sla PNG is one HTTP call and zero parsing. If your destination needs the underlying numbers (per-severity counts, severity-weights breakdown), the /sla_report JSON is the only path — the PNG does not carry the structured data.

How the SLA colour is computed

The SLA colour is not a direct severity-to-colour mapping — it is computed across the dataset's tests by SLACalculator based on which severities have failing tests:

  • Red — at least one Critical test is failing, OR all Major-severity tests are failing, OR a particular all-but-one-Major-failing-and-all-Minors-failing pattern.

  • Yellow — some Major tests failing (but not all), OR all Minor tests failing, OR no tests at any severity defined yet (the platform errs cautious when nothing is defined).

  • Green — none of the above; passing tests dominate at every severity.

So changing a single test's severity from Major to Critical can flip the dataset from Yellow to Red without any test pass / fail status changing. Use severities to encode "how loud should this dataset's failure be" rather than as a labelling exercise.

Known operator caveats

Where to next

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