Derive insights on your data quality by our metrics.
Transform Reactive Fire-Fighting into Proactive Data Trust
Decube's Data Quality module empowers your team to shift from reactive incident response to proactive data trust. Our ML-powered monitoring system detects anomalies before they impact downstream systems, AI/ML models, and business decisions.
Why Data Quality Monitoring Matters
🚨 Early Detection: Catch data issues before they cascade downstream
🤖 AI-Ready Data: Ensure clean inputs for accurate ML models and AI systems
📊 Business Confidence: Make decisions based on trusted, validated data
Grouped-By - Segment monitoring by dimension values
🎯 Monitor Modes
Scheduled: Continuous monitoring with configurable frequency
On-Demand: Manual execution for ad-hoc validation
Incident Overview
Understanding Incidents
Data Quality incidents are automatically triggered when monitors detect anomalies or threshold violations. Each incident provides detailed context to help you understand and resolve data quality issues quickly.
Incident Details
Our monitoring system categorizes incidents into six main types:
Type
Purpose
Use Case
Freshness
Data update delays
Critical for real-time dashboards and daily reports
Volume
Unexpected row count changes
Detect missing data loads or data pipeline issues
Field Health
Column-level data quality
Validate nulls, uniqueness, ranges, and patterns
Schema Drift
Table structure changes
Prevent downstream application failures
Custom SQL
Business rule violations
Monitor complex business logic and data relationships
Job Failure
ETL pipeline failures
Ensure data transformation processes complete successfully
Incident Overview
Incident Details
Incident Management Workflow
Incident Overview
The incident dashboard provides a consolidated view of all data quality issues across your organization.
Incident Overview Dashboard
Incident Details & Investigation
By selecting any incident from the Data Quality module, users will be redirected to the Incident Details page. This page provides you with a deeper understanding of and historical trend of the chosen incident.
Key Features:
📋 Assignee Management: Assign incidents to team members for accountability
📈 Historical Trends: View patterns and frequency of similar incidents
🔍 Root Cause Analysis: Access detailed metrics and context
📝 Audit Trail: Track all actions and changes in the incident lifecycle
Example of a Custom SQL incident — Add Assignee functionality, with actions tracked in Audit History
On the Incident Details page, you can add an Assignee to the selected incident. All such actions will subsequently be logged and can be reviewed in the Audit History section on the bottom right.
Incident Status Management
When an incident is raised, it creates an open incident. You can choose to either:
Close an incident when resolved
Mute it for a specified time period to prevent alert fatigue
Muting ensures you don't get duplicate alerts when another incident is triggered on the same table/column. Incidents are automatically unmuted after the time period you have set.
Example of a Custom SQL incident that is currently open on right panel
To view open, closed, or muted incidents, click 'Apply Filters' on the Incidents Overview page and select the appropriate checkboxes under 'Incident Status'.
Filter incidents by status
Advanced Investigation Tools
Historical Analysis
In the History tab, a list of past tests is shown, including the metrics of successful scans. This is a quick way to identify the scans that had failed along with the values that had caused the failed tests.
Use Cases:
📊 Pattern Recognition: Identify recurring issues and trends
⚖️ Threshold Validation: Verify if alert thresholds are appropriate
🔄 Root Cause Analysis: Understand what changed to cause failures
Example of a History section for a Field Health incident.
Impact Assessment
Based on the downstream lineage, a list of impacted assets is able to be generated to show to the user the potential downstream tables or jobs or dashboards that may be affected by the incident. Users can then opt to export this list as a CSV and send them to the respective owners that were designated in the Catalog.
Key Benefits:
🎯 Targeted Communication: Know exactly who to notify about data issues
📈 Business Impact: Understand which reports and dashboards may be affected
⚡ Faster Resolution: Prioritize fixes based on downstream impact
Example of the list of assets impacted by the Custom SQL incident
Continued list of assets impacted by the Custom SQL incident
