Most organisations don’t lose trust in data because of bad intentions or poor tooling.
They lose trust because expectations are implicit, undocumented, and constantly shifting.
In this episode, Roland Brown takes one of the most talked about and least understood concepts in modern data architecture and brings it firmly down to earth: data contracts. Building on the ownership and accountability foundations laid in Episode 65, he explains why trust does not emerge organically in complex data environments and why contracts are the mechanism that makes trust operational.
Roland challenges the common misconception that data contracts are a technical artefact or a schema enforcement tool. Instead, he reframes contracts as explicit agreements between producers and consumers agreements about meaning, quality, freshness, availability, and change. Without these agreements, even well-owned data products slowly decay into ambiguity and workarounds.
The episode explains how most organisations already have implicit contracts hidden in Slack messages, tribal knowledge, and one-off explanations and why making those expectations explicit is the difference between fragile trust and reliable confidence.
Roland walks through what a practical data contract actually includes:
• what the data represents not just its structure
• which decisions it supports
• how fresh it is expected to be
• what “good enough” quality means in context
• what happens when expectations are not met
• how changes are communicated and versioned
Crucially, the episode makes clear that contracts are not about rigidity or perfection. They are about predictability. Consumers do not need flawless data they need to know what they can rely on, when, and why.
Drawing on Episode 62’s product anatomy, Roland shows how contracts strengthen every component of a data product:
• Intent stops being aspirational and becomes enforceable
• Ownership becomes real because expectations are explicit
• Semantics stabilise because definitions are agreed, not inferred
• Quality shifts from abstract targets to decision-level fitness
• Interfaces become safer because usage expectations are clear
• Lifecycle management becomes possible because change is governed
A practical example illustrates how revenue data without contracts leads to endless reconciliation, duplicated logic, and mistrust while the same data, under a clear contract, becomes a stable input into forecasting, reporting, and compliance decisions.
The episode also addresses a common fear: that contracts will slow teams down. Roland explains why the opposite is true. By reducing interpretation, clarification, and rework, contracts actually accelerate delivery and adoption while protecting consumers from silent breaking changes.
The episode closes with a powerful reframing:
data contracts are not bureaucracy they are care.
Care for consumers.
Care for decisions.
Care for trust over time.
When contracts are explicit, trust stops being personal and starts becoming systemic.
Discover insights on:
• Why trust cannot be scaled without explicit expectations
• What data contracts really are beyond schemas and tooling
• The practical components of a usable data contract
• How contracts protect both producers and consumers
• Why predictability matters more than perfection
• How contracts make ownership and accountability real
“Trust doesn’t come from knowing who to ask.
It comes from knowing what to expect.”
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