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

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"    }  ]}
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