# Data Contracts

Codify trust between teams with enforced data guarantees

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![](data:image/svg+xml,%3csvg%20xmlns=%27http://www.w3.org/2000/svg%27%20version=%271.1%27%20width=%271400%27%20height=%27600%27/%3e)![Data Contracts](/_next/image?url=%2Fimages%2Fdata-contracts%2Fdata-contracts-header.png&w=3840&q=75)

![](data:image/svg+xml,%3csvg%20xmlns=%27http://www.w3.org/2000/svg%27%20version=%271.1%27%20width=%2744%27%20height=%2744%27/%3e)![Prevent late night production fires](data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7)

![Prevent late night production fires](/_next/image?url=%2Fimages%2Fdata-contracts%2Fcard-prevent-fires.png&w=96&q=75)

Prevent late night production fires

Catch breaking schema, quality, and SLA changes before they reach production

![](data:image/svg+xml,%3csvg%20xmlns=%27http://www.w3.org/2000/svg%27%20version=%271.1%27%20width=%2744%27%20height=%2744%27/%3e)![Contracts for your whole team](data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7)

![Contracts for your whole team](/_next/image?url=%2Fimages%2Fdata-contracts%2Fcard-whole-team.png&w=96&q=75)

Contracts for your whole team

Technical users work in YAML, business users in no-code UI, on the same contract

![](data:image/svg+xml,%3csvg%20xmlns=%27http://www.w3.org/2000/svg%27%20version=%271.1%27%20width=%2744%27%20height=%2744%27/%3e)![Open standard portability](data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7)

![Open standard portability](/_next/image?url=%2Fimages%2Fdata-contracts%2Fcard-open-standard.png&w=96&q=75)

Open standard portability

Import and export contracts in Open Data Contract Standard (ODCS) 3.1, no lock-in

## Prevent late night production fires

Validated continuously against your live data with no extra infrastructure

Continuous Validation

Collate checks every contract against live data on a configurable schedule and on demand, with native tooling.

Data Quality Assertions

Enforce table and column tests: uniqueness, null checks, referential integrity, and custom rules, from native Data Quality tests.

Automatic Incidents and Alerts

Failed tests flag the contract as violated, open an incident, and notify owners in Slack, Teams, email, or webhooks.

SLA and History Tracking

Track freshness, latency, and retention targets over time, with run-by-run charts showing what passed, failed, or was aborted.

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![\[object Object\]](/_next/image?url=%2Fimages%2Fdata-contracts%2Fcatch-breaks-before-they-reach-you.png&w=3840&q=75)

## Contracts for your whole team

YAML for engineers, no-code UI for everyone else, on one shared contract

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YAML and No-Code UI

Engineers work with contracts in YAML; business users in the no-code UI. Same contract, the right tool for each user.

Granular Schema Contracts

Contract only the columns you depend on. Lock the specific fields you rely on and let the others evolve freely.

Semantic Rules

Require owners, descriptions, tags, and domains as contract rules, so data stays usable after its authors move on.

Approval Workflows

Every contract can be reviewed and approved before enforcement, so it carries real buy-in across teams.

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## Open standard portability

Built on ODCS 3.1 and ready to extend from tables to your whole platform

ODCS 3.1 Import and Export

Import and export in Open Data Contract Standard, JSON or YAML. Collate's model is an ODCS superset, keeping detail others drop.

Coverage Across Entity Types

Start with tables for full schema, quality, and semantics, then extend contracts to topics, dashboards, ML models, and more.

Data Product Inheritance

Assets inside a data product inherit its contract's semantics, SLA, and security, with asset-level contracts taking precedence.

API and SDK Access

Create, validate, and export contracts programmatically through the REST API or the Python and Java SDKs.

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## Built for modern data & AI practices

Designed for changing needs of data & AI teams

AI-Driven Automation

Improve productivity, enforce governance and reduce costs with AI driven automation

Unified Platform

One platform for all your teams for data discovery, observability and governance

Collaborate Around Data

Accelerate development of data assets with social workspaces and knowledge centers

Get started with Collate today for free

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Managed Service for Production Data Teams

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## FAQs

Expand All

What is a data contract in Collate?+

A data contract is a formal, versioned agreement about what a data asset will deliver: its schema, semantics, quality, SLAs, security, and terms of use. In Collate, a contract is not a static document. It is a tracked object validated continuously against your live data, so producers and consumers share one enforceable definition instead of an informal assumption.

How is Collate different from YAML-only data contract tools?+

Most tools force a choice between technical rigor and business accessibility. YAML-only tools exclude the domain experts who understand what data should mean. Editable documents include everyone but have no enforcement mechanism. Collate closes both gaps: engineers work in YAML while business users work in the no-code UI, on the same contract. And every contract is continuously validated against live data, so it actively catches violations instead of sitting in a wiki as static documentation.

How do teams create and manage data contracts in Collate?+

Any Collate user can draft a contract. Engineers use YAML or the REST API and Python and Java SDKs, and domain experts and analysts use the no-code UI. Both paths edit the same contract, share one validation history, and produce one enforcement record.

Before a contract goes into enforcement, it goes through the same approval workflow and review process used for glossary terms. This ensures contracts carry real sign-off from the teams accountable for the data. Approvers are configured per domain or asset type, keeping governance consistent without centralizing every decision through a single team.

What happens when a data contract is violated?+

When a quality test fails or the schema is improperly modified, Collate marks the contract as violated, automatically opens an incident, and notifies owners through their existing channels: Slack, Teams, email, or webhooks. Stakeholders get context on what broke and which downstream assets are affected, so a violation becomes a fast fix instead of a 2 a.m. surprise.

Which data assets can have contracts?+

Contracts start with tables, where Collate validates schema, quality, and semantics in full. Semantics and schema rules also extend to topics, API endpoints, and dashboard data models. Semantics rules reach across dashboards, charts, pipelines, ML models, containers, and more. Coverage continues to expand release over release.

Contracts also apply at the data product level. When a data product has a contract, every asset inside it inherits the contract's semantics, SLA, terms of use, and security rules. An individual asset can still carry its own contract, which takes precedence over the inherited one, making contracts a natural fit for a data mesh, where guarantees follow the domain.

Does Collate support the Open Data Contract Standard (ODCS)?+

Yes. Collate imports and exports contracts in ODCS version 3.1, in both JSON and YAML, with smart-merge and full-replace modes. Collate's contract model is a superset of ODCS 3.1, so you can export in portable ODCS format for use across tools or in native format to keep the extra detail Collate captures.

How do data contracts relate to Collate's Data Quality features?+

Data contracts are built on top of native Collate Data Quality capabilities, not a separate engine. When you add quality assertions to a contract, you select from the same test framework used everywhere else in Collate: uniqueness, null checks, referential integrity, and custom business rules. Results appear in the same dashboards, and a failing test escalates straight to the contract.

How do data contracts interact with lineage?+

When a contract is violated, Collate uses lineage to show which downstream assets are affected, such as dashboards, pipelines, ML models, and other tables that depend on the breached asset. This means stakeholders don't just learn that something broke; they see what's at risk. Platform teams can prioritize resolution based on actual downstream impact rather than guessing which consumers matter most.