2026-07-12·8 MIN READ·#data#contracts#platform

DATA CONTRACTS THAT STICK: OWNERSHIP, FRESHNESS, AND BREAKING-CHANGE DISCIPLINE

How to implement data contracts enterprises actually keep: owners, SLAs, schema evolution, and tests in CI - not wiki pages nobody reads.

A data contract is an explicit agreement between producers and consumers: schema, semantics, freshness, and what happens on break. Contracts stick when they live in code with owners and CI checks - not in a Confluence page last edited during a reorg.

Minimum viable contract

  • Owner (team + pager path)
  • Schema with compatibility rules (backward/forward)
  • Freshness and completeness SLOs
  • Consumer list and intended grain/semantics
  • Change process: how breaks are proposed, reviewed, versioned

Put tests where deploys happen

Contract tests in the producer pipeline catch breaks before dashboards lie. Consumer contract tests catch silent semantic drift. Pair with a catalog so discovery and ownership stay linked - see /products/data-platform and /solutions/data.

Evolution without chaos

Prefer additive changes. Deprecate with dates. Dual-write or dual-read during migrations. Never 'sneak' a semantic change under the same field name - that is how month-end becomes archaeology.

If nobody owns freshness, you don't have a contract - you have a hope.

FAQ

Quick answers

What is a data contract?

A producer-consumer agreement covering schema, meaning, freshness, and break protocol - enforced in code and CI, with a named owner.

How do data contracts fail?

Wiki-only contracts, missing owners, and silent semantic changes under unchanged field names.