Data Quality
Trusted Data for Every Decision
Yavantha helps organizations continuously monitor, manage, and improve data quality — ensuring analytics, operations, and AI are built on reliable data.
Proactive Quality Monitoring
Detect issues before they impact reports, dashboards, or AI models.
- Rule-based checks for accuracy, completeness, and consistency
- Automated anomaly detection
- Real-time alerts to the right teams
- Continuous monitoring across systems
Rule-Based & Intelligent Validation
Combine business rules with intelligent automation.
- Business-defined validation rules
- AI-assisted quality rule suggestions
- Context-aware checks using lineage and usage
- Adaptable to changing data patterns
Collaborative Issue Resolution
Resolve data quality issues across teams with clarity and accountability.
- Assign and track issues with workflows
- Collaborate with comments and history
- Document root causes and fixes
- Create shared ownership of quality
Quality Metrics That Matter
Measure, track, and communicate quality improvements.
- Quality scores by domain, source, or owner
- Trends over time
- Impact analysis on downstream systems
- Executive-ready dashboards
Data Quality Lifecycle
01
Define
Define quality rules, thresholds, and expectations.
02
Measure
Continuously assess data quality and business impact.
03
Remediate
Assign issues, collaborate, and resolve root causes.
04
Improve
Track trends, optimize rules, and prevent future issues.
Yavantha turns data quality into a continuous, measurable, and collaborative improvement lifecycle.
