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Data Anomaly Policy - Schema

Data Anomaly (profile anomaly) policy

Execution result endpoints for anomaly detection use separate result schemas.

Top-level Fields

Depending on the endpoint, anomaly policy responses carry configuration in one or both of:

Field

Type

Description

details

object

Rule-level details including policy items (metrics to monitor, thresholds, etc.).

assetConfiguration

object

Asset-level configuration for anomaly detection (profiling type, schedule, owner/team, pattern settings).

manualProfilingTriggers

array

Reasons and flags controlling when manual profiling is required or blocked.

Key nested properties (high-level):

  • details.backingAssetId (integer) – Asset the anomaly policy is configured for.

  • details.items[] – Individual anomaly checks (per metric/column).

  • assetConfiguration.profilingType (string) – Type of profiling (for example distribution, volume, etc.).

  • assetConfiguration.schedule / scheduled (string / boolean) – When anomaly profiling runs.

  • assetConfiguration.notificationChannels (string or object, depending on shape) – High-level alerting configuration.

  • manualProfilingTriggers[].canTrigger (boolean) – Whether manual profiling is allowed.

  • manualProfilingTriggers[].reason (string) – Human-readable reason.

  • manualProfilingTriggers[].type (string) – Trigger type.

Example JSON

{
 "details": {
 "backingAssetId": 7456771,
 "continueExecutionOnFailure": false,
 "executionSequence": 1,
 "filter": null,
 "id": 23001,
 "isCompositeRule": false,
 "isSegmented": false,
 "items": [
 {
 "businessExplanation": "Detect anomalies in daily order volume.",
 "columnName": "order_date",
 "executionOrder": 1,
 "id": 34001,
 "ruleId": 23001,
 "ruleVersion": 1,
 "weightage": 100
 }
 ]
 },
 "assetConfiguration": {
 "profilingType": "VOLUME",
 "owner": "data-team@company.com",
 "team": "Data Platform",
 "schedule": "0 * * * *",
 "scheduled": true,
 "timeZone": "Asia/Kolkata",
 "patternConfiguration": {
 "frequencyType": "DAILY",
 "maxPatterns": 10
 },
 "notificationChannels": "DEFAULT",
 "minimumRequiredHistoricalMetricsForAnomalyDetection": "7d",
 "referenceCheckConfiguration": "LATEST",
 "sparkResourceConfig": "DEFAULT",
 "persistencePath": "s3://bucket/path/anomaly-metrics",
 "updatedAt": "2024-06-18T12:32:30.415Z"
 },
 "manualProfilingTriggers": [
 {
 "canTrigger": false,
 "reason": "Insufficient historical data for anomaly detection.",
 "type": "HISTORICAL_DATA_INSUFFICIENT"
 }
 ]
}