Ensuring quality often means fragmented tools, bolt-on monitoring, and slow incident response. With Coalesce Quality, data quality is embedded directly into transformation and catalog workflows—so you can test before merge, monitor in production, and resolve issues with full lineage context. The result: fewer incidents, faster fixes, and provable reliability.
Catch issues pre-merge—not post-incident
Build testing into your development workflow. Define tests, contracts, and SLOs at the node and column level. Gate deployments on pass criteria so bad data never reaches production.
- Author tests alongside transformations in CI/CD-aware projects
- Block merges and releases when critical tests or SLOs fail
- Capture approvals with lineage for auditability
- Manage tests using bulk operations and unified grids
Monitor freshness, volume, and distribution—automatically
Automate anomaly detection and trigger lineage-aware alerts to surface issues early. When something breaks, teams see the blast radius immediately—with owners, SLAs, and root-cause context in one place.
- Detect schema, volume, freshness, and distribution anomalies automatically
- Get actionable, grouped alerts enriched with lineage and owner context
- Assign and resolve incidents using built-in workflow management
- Track SLAs and measure Data Downtime with policy-driven monitoring
Quality you can prove, not hope for
Centralize governance with contracts, reusable templates, and policy-driven SLAs that scale across teams and domains. Rules are suggested by AI from metadata and auto-attached to lineage—so standards are enforced, not just documented.
- Define schema/column contracts, freshness checks, and business-rule tests per node
- Enforce consistency with org-wide standards libraries and templates
- Inherit rules automatically through lineage—no manual re-configuration
- Formalize data quality contracts between producers and consumers
Surface trust where analysts and AI agents work
Connect tests, lineage, and impact into unified dashboards. Surface quality scores, owners, and run history in the Catalog—so analysts and AI agents can prefer “green” assets automatically.
- Monitor health with dashboards by pipeline, domain, and owner
- Track progress with trend analytics and reliability KPIs
- Analyze real-time downstream impact powered by automated metadata sync
- Give consumers confidence with quality badges and certification status
Fragmented stacks create blind spots—broken metrics, brittle handoffs, and slow incident response. Embedding quality where code is born means you catch issues pre-merge, tie failures to lineage and owners, and resolve faster. Teams report fewer incidents and faster delivery cycles.
Yes. Automated anomaly detection monitors schema changes, volume shifts, freshness delays, and distribution anomalies. Alerts are enriched with lineage, owners, and SLA context so teams can act before dashboards or AI outputs are impacted.
Define contracts and checks at the node/column level, then inherit them automatically through lineage. Policies are enforced at deploy time—not just documented—so quality scales across domains and teams without slowing delivery.
Unified dashboards show adoption, quality health by domain, data downtime trends, and real-time downstream impact when issues occur. Quality scores and badges surface in Catalog, giving leaders provable reliability metrics for the board.
Experience the power of Coalesce Quality
Design, validate, and monitor pipelines end-to-end to turn fragmented processes into a single, reliable path from pipeline to proof.
