Day: April 10, 2026

Buck Woody becomes accountable:

A businessperson pulls a report from a data warehouse, runs the same query they’ve used for two years, and gets a number that doesn’t match what the finance team presented at yesterday’s board meeting. Nobody changed the report. Nobody changed the dashboard. But somewhere upstream, an engineering team renamed a field, shifted a column type, or quietly altered the logic in a pipeline, and nobody thought to mention it because there was no mechanism to mention it.

While we think of this as an engineering failure, it’s more of an implied contract failure. More precisely, it’s the absence of a formal contract. Data contracts are one of the most practical tools a data organization can adopt, and one of the most underused. The idea is not complicated: a data contract is a formal, enforceable agreement between the team that produces data and the team that consumes it. It defines what the data looks like, what quality standards it must meet, who owns it, and what happens when something changes. Think of it as the API layer for your data, the same guarantee a software engineer expects from a well-documented endpoint, applied to the datasets and pipelines your business depends on. This post is about why that matters at the CDO level and how to get them put in place.

Click through to learn more about what data contracts are and why they are useful. This post stays at the architectural level rather than the practitioner level, but lays out why it’s important to think about these sorts of things.