Anomaly Status¶
Reviewing anomaly status
Every anomaly carries a status that tracks its lifecycle stage, from initial detection to final resolution. Statuses split into two groups: Open, for anomalies that still need attention, and Archived, for anomalies that have been resolved, dismissed, or categorized for reference.
To filter the anomaly list by these groups in the UI, see the status tabs.
Status colors¶
Each status has a distinctive color, kept consistent across the UI (anomaly lists, details views, and notifications). The icon next to a status can change by context, but the color stays the same. The legend below shows the color associated with each status:
| Icon | Status | Description |
|---|---|---|
| Active | Unresolved and awaiting triage. | |
| Acknowledged | Reviewed, still needs follow-up. | |
| Resolved | Legitimate concern that has been addressed. | |
| Duplicate | Same issue as another anomaly. | |
| Invalid | Not a real data quality concern. | |
| Discarded | No longer relevant or under review. |
Open Anomalies¶
Open anomalies are issues that have been detected but not yet resolved or archived. They have two sub-statuses:
| Status | Description |
|---|---|
| Active | Newly detected and unresolved. Has not been acknowledged, archived, or resolved. May require immediate attention. |
| Acknowledged | Reviewed and acknowledged by someone, but still needs further action. |
To view every open anomaly at once regardless of sub-status, use the All subtab in the anomaly list. See the status tabs.
Archived Anomalies¶
Archived anomalies have been reviewed and moved out of active monitoring. They are categorized by how they were resolved or classified, keeping a clean historical record without cluttering the active list. They have four sub-statuses:
| Status | Description |
|---|---|
| Resolved | Was a legitimate data quality concern, now addressed. |
| Duplicate | A duplicate of another anomaly that has already been addressed. |
| Invalid | Not a legitimate concern; no further action required. |
| Discarded | No longer relevant or under review. Removes outdated entries without marking them as Invalid or Resolved. |
To view every archived anomaly at once regardless of sub-status, use the All subtab in the anomaly list. See the status tabs.
What happens when an archived anomaly is detected again
Every archived status removes the anomaly from the open list, but they behave differently when a later scan detects the same fingerprint:
- Duplicate: the archived anomaly is never reopened. A new detection still creates a new Active anomaly, so Duplicate does not silence the issue if it returns.
- Resolved, Invalid, and Discarded: when the scan runs with both Archive Duplicate Anomalies and Reactivate Recurring Anomalies turned on, the archived anomaly is reopened as Active and the new detection is marked Duplicate.
You do not need to reference an "original anomaly ID" when archiving as Duplicate. Anomalies that share a fingerprint are linked to the earliest one, which shows each later one on its Timeline. See Related Anomalies and Anomaly Fingerprints for the matching criteria and the re-opening option.
Note
For step-by-step instructions, see Archive Anomalies or Restore Anomalies.
See Also¶
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Assignees
How the Assignees field works, who can be assigned, and when assignees are notified.
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Fingerprints
How Qualytics recognizes a newly detected anomaly as a duplicate of one it already found.
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Anomaly Views
The four screens that show anomalies: how to reach each one, what it shows, and what you can do there.
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Description
The business-friendly explanation of the data quality issue behind an anomaly.
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Source Records
The rows behind an anomaly, how to read them, and how masked values are protected.
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Tickets
Linked Jira and ServiceNow tickets: sync modes, what reaches the ticket, and status sync.
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Timeline
The record of every change to an anomaly, and how comments and mentions work.
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Examples
Real scenarios that follow an anomaly from the Scan that finds it to the decision that closes it.
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Best Practices
Guidelines for keeping the anomaly list short, trusted, and acted on.
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Permissions
The team permission and user role behind every anomaly action.
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How It Works
How a Scan creates anomalies, AI Managed and Authored checks, the lifecycle, duplicates, and notifications.
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Record Anomalies
Anomalies that flag one row: when they are created, how rows are grouped, and examples.
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Shape Anomalies
Anomalies about many rows or the whole dataset: what creates them, what they count, and examples.
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AI Managed and Authored
How anomalies from AI Managed and Authored checks differ, the AI badge, and how triage tunes AI Managed checks.
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Impact
How the Low to Critical impact level is decided from the failed checks, and when it updates.