Gap

YAML type: gap | Category: Data quality

Detects missing-data intervals between consecutive dates in a series.

Description

The Gap detector looks for holes in the time axis -- periods where expected daily points are absent. It is a data-quality detector, not a value-shape detector. Use it to catch broken loads, incomplete extracts, or upstream pipeline outages.

How it works

Gap illustration

Gap walks the series date axis and looks for holes between consecutive observed days. When the empty stretch is longer than longerThan (and within optional shorterThan bounds), it emits a Gap anomaly.

It does not score the metric values themselves -- only whether expected calendar days are missing after load. That makes it a freshness / pipeline-completeness check rather than a shape detector.

Setup

Add a gap detector under analysis.detectors in the data view YAML (or Analysis tab). Tune longerThan so short expected holidays do not fire, and use series filters to ignore low-volume series.

Configure detectors on the data view Analysis tab or in YAML. Validate with Data Preview before enabling production schedules.

Settings

Parameter	Default	Description
`longerThan`	`3`	Flag gaps longer than this many days
`shorterThan`	`0`	Optional upper bound for gap length reporting

Shared series filters

Most detectors also accept optional series filters in params:

Parameter	Purpose
`maxGapAmount`	Skip series when gap amount is too high (`null` = no limit). Catalog create-default is often `5`.
`minValue`	Skip series whose average value is below this (`null` = no limit). Catalog create-default is often `1000`.
`maxValue`	Skip series whose average value is above this (optional; omit/`null` = no limit)
`useSpecialDates`	When `true`, suppress anomalies that overlap special dates

When a filter skips a series, Data Preview shows the reason.

Configuration example

analysis:
  detectors:
    - type: gap
      params:
        longerThan: 3
        shorterThan: 0

Using the detector

Review Gap anomalies on Home after load jobs. Investigate whether the source query, connector, or warehouse had an outage for the gap window.

Use cases

Daily sales or traffic feeds that must arrive every calendar day
Detecting silent failures where load succeeds but returns no rows for some dates
SLA monitoring for warehouse freshness at the series level

Specifics

Gap detection runs on the series date axis after load. Combine with stale for end-of-series freshness.

Gap