Data Quality

Improve, monitor and fix data quality with Semarchy

Q: What is the difference between monitoring and enforcing data quality?

Monitoring happens at the catalog level: KPIs, dashboards and anomaly alerts show how healthy each Data Product is. Enforcement happens at the record level, stopping a bad or duplicate value at the point of entry. Semarchy does both, in one platform, from the same rule definitions.

Q: How is data quality enforced at the record level in real time?

Every Data Product ships with built-in real-time certification APIs, and data apps validate inline. Any app or system of record can check for duplicates and rule violations before a record is created — across hundreds of sources and millions of records, with sub-60ms response times.

Q: What does Certification do to my source data?

Certification turns integrated source data into governed golden and master records — enrichment, validation, match and merge, and quality rules. It is one generated process defined at design time, not separate tools stitched together, so trust is built in rather than reconciled later.

Q: Can AI help write data quality rules or resolve violations?

Yes, with a person still accountable. Semy can draft a rule in SemQL for a steward to review, and an embedded Data Product agent can build quality dashboards and suggest improvements. Those recommendations are read-only — a steward approves the change, and lineage records who made it.

Q: How do I prove which rules were applied to a golden record?

Every policy and action applied to a record is tracked from source to golden. Golden and master record history, validation errors and audit logging stay reviewable in the Data Product’s web UI, so nothing is overwritten silently and audit, compliance and impact analysis are self-serve.

Data quality policies automatically enforced, issues easily resolved, semantic drift stopped before it reaches any dashboard or agent action

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Automated certification with real-time quality enforcement

Monitor and fix data quality issues when they happen or automatically enforce data quality in real-time before they become issues.

Automated data certification

Medallion architecture-based process transforming raw data into golden records — enrichment, match, merge, survivorship with record-level lineage

Real-time data quality

Stop duplicates and rule violations at the point of entry — real-time APIs and in-app UI check, certify or block records before they are created

Monitor and fix data quality

Dashboards, KPIs and anomaly alerts in your data apps, with dynamic task routing so the right teams are notified and resolve issues immediately

Data quality monitored monitored + enforced, automatically

Custom rules, continuous certification, flexible enrichment, real-time enforcement, monitoring and stewardship — inside every Data Product.

Create custom, transparent data quality rules + policies

Turn business logic into enforceable rules with SemQL, or let Semy draft them. Every policy and action on a record is visible from source to golden.

Create data quality rules

Define required fields, match logic, transformations, enrichers, constraints, referential integrity checks and resolution workflows in SemQL.

Transparency + lineage

Teams and agents see exactly which rules, policies and actions hit each record, with source-to-golden change tracking in the Data Product’s UI.

Automatically certify data and prevent context drift

Golden record semantics, context and quality rules live and travel with the data product, not in downstream prompts so agents stay accurate without drifting.

Data certification process

SDP creates and certifies golden records from every source, applying your quality rules and enrichers to build one source of truth for any domain.

Agent drift prevention

Rules, semantics, context and reasoning instructions are embedded at design time — not added downstream — so agents on MCP stay accurate.

Flexible data enrichment processes and crosswalks

Close quality gaps with built-in plugins, third-party providers and custom GenAI enrichers. A registry of Global IDs keeps crosswalks current.

Flexible data enrichment

Use 150+ built-in enrichment plugins, your own third-party providers or custom GenAI enrichers — automated, or routed for review, approval and edits.

Mappings + crosswalks

A real-time, centralized registry of unique Global IDs harmonizes and syncs internal and external reference data — even with complex hierarchies.

Real-time data quality enforcement – anywhere

Stop issues at the moment of creation, not in downstream cleanup jobs. Steppers guide multi-team workflows; real-time APIs check any app or system.

In-App UI/UX

Configure steppers to split complex, multi-team workflows into guided steps, preventing violations at entry with error messages and predefined LoVs.

Real-time APIs

Each Data Product’s built-in APIs check for duplicates and violations before a record is created — hundreds of sources, <60ms response times.

Continuous data quality monitoring and alerts

Track quality and health with customizable KPIs and dashboards in-platform or in your BI tool, and route alerts straight to the steward’s inbox.

Custom dashboards

See a Data Product’s quality and health at a glance with built-in dashboards for data quality and operational analytics — or publish to your BI tool.

Continuous monitoring

Automated alerts on anomalies and violations assign tasks by email, or notify Slack, Teams and other enterprise apps through our APIs.

Fix and improve data quality with workflows and agents

Resolve issues as a team with a shared inbox, dynamic assignment, multi-party approvals and full action tracking — no hand-offs or email chains.

Multi-team workflows

An inbox, manual or dynamic task assignment, multi-party approvals, comments, action tracking and progress monitoring resolve DQ issues at scale.

Embedded DQ agents

Ask an in-app Data Product agent for dashboards and improvement suggestions, or use MCP to ask directly in Snowflake Cowork, Copilot and Claude.

See how customers improve data quality with Semarchy

Enterprises across industries are leveraging DataOps in SDP to scale their data product delivery, increase agility and to trusted insights

Semarchy has really evolved with our company. The product's agility and flexibility let us go where the business takes us, expanding it into more of a strategic MDM solution than what we started with.

Hogan Le

Senior Manager, Governance and BI Systems, Chipotle

Semarchy's implementation strategy is one of the best I've ever dealt with. We never had to bring in an outside partner. They provided great training, support, and project management. I can't say enough for how impressed I am.

James Wilson

VP of Analytics and Enterprise Solutions, Rexel USA

See all customer success stories

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