> For the complete documentation index, see [llms.txt](https://docs.decube.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.decube.io/data-quality/data-quality.md).

# Incidents Overview

Decube's Data Quality module monitors your data assets continuously, detects anomalies automatically, and surfaces incidents so your team can investigate and resolve issues before they affect downstream consumers.

## Monitor Types

Each monitor type targets a specific category of data quality issue. Click through to the setup guide for the monitor you want to configure.

| Monitor          | What it detects                                              | Setup guide                                                                                                 |
| ---------------- | ------------------------------------------------------------ | ----------------------------------------------------------------------------------------------------------- |
| **Freshness**    | Data that has stopped updating within an expected window     | [Set up Freshness monitors](/data-quality/how-to-set-up-monitors/set-up-freshness-monitors.md)              |
| **Volume**       | Unexpected changes in row counts                             | [Set up Volume monitors](/data-quality/how-to-set-up-monitors/set-up-volume-monitors.md)                    |
| **Field Health** | Column-level anomalies — nulls, uniqueness, ranges, patterns | [Set up Field Health monitors](/data-quality/how-to-set-up-monitors/set-up-field-tests.md)                  |
| **Schema Drift** | Table structure changes                                      | [Set up Schema Drift monitors](/data-quality/how-to-set-up-monitors/set-up-schema-drift-monitors.md)        |
| **Custom SQL**   | Business rule violations defined by custom SQL logic         | [Set up Custom SQL monitors](/data-quality/how-to-set-up-monitors/custom-sql-monitors.md)                   |
| **Job Failure**  | ETL pipeline job execution failures                          | [Set up Job Failure monitors](/data-quality/how-to-set-up-monitors/set-up-data-job-job-failure-monitors.md) |
| **Grouped-By**   | Quality issues segmented by dimension values                 | [Set up Grouped-By monitors](/data-quality/how-to-set-up-monitors/set-up-grouped-by-monitors.md)            |

Monitors run in two modes: **Scheduled** (continuous, at a configurable frequency) and **On-Demand** (manual, for ad-hoc validation).

## Getting Started

1. [Enable asset monitoring](/data-quality/enable-asset-monitoring.md) on the tables you want to cover.
2. [Set up alert notifications](/alert-notifications/notification-alerts.md) so your team is notified when incidents are triggered.
3. Review [Incident Details](/data-quality/data-quality/incident-details.md) to understand what each incident shows you and how to investigate.
4. Review [Managing Incidents](/data-quality/data-quality/incident-management.md) to learn how to close, mute, and bulk-update incidents.

{% content-ref url="/pages/f7SehvK9kQi9RYPSSxru" %}
[Available Monitor Types](/data-quality/available-monitor-types.md)
{% endcontent-ref %}

## Related Pages

{% content-ref url="/pages/JwDGUfWup3P1TQWUn9zw" %}
[Incident Details](/data-quality/data-quality/incident-details.md)
{% endcontent-ref %}

{% content-ref url="/pages/ZayzgoP6LWwmhawZ0z1U" %}
[Managing Incidents](/data-quality/data-quality/incident-management.md)
{% endcontent-ref %}

{% content-ref url="/pages/cFfu9PDAnjRwAkZxU098" %}
[Config Settings](/data-quality/config-settings.md)
{% endcontent-ref %}

{% content-ref url="/pages/oHQMBTOmZQevImaIjmyw" %}
[Incident model feedback](/data-quality/data-quality/incident-model-feedback.md)
{% endcontent-ref %}

{% content-ref url="/pages/AuBPzQbjZY9jvr7I4oRR" %}
[Asset Report: Data Quality Scorecard](/reports/asset-report-data-quality-scorecard.md)
{% endcontent-ref %}


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