A data product is more than just a dataset. It’s a well-defined, reusable, and governed asset—delivered with the same care and clarity as a software product.

Each data product is built and maintained by a domain team that understands the context of the data. It includes its own documentation, lineage, access methods, and most importantly, a clear agreement between those who produce the data and those who consume it.

This agreement is referred to as the data contract.

Data contracts formalize the relationship between producers and consumers. They define what the data is, how it can be accessed, how often it updates, what level of quality is expected, and who is allowed to use it.

This alignment is critical. It prevents surprises, reduces friction, and allows both sides to operate with confidence. Without it, teams waste time clarifying expectations, rebuilding broken pipelines, or fixing misunderstandings after the fact.

With a contract in place, data can be made "ready once, at the source", instead of being cleaned and validated repeatedly downstream.

AI and machine learning rely on consistent, high-quality input. Yet most organizations still struggle with data that’s brittle, undocumented, or inconsistently governed. Without reliable data foundations, even the most advanced models underperform.

Data products provide a scalable approach to delivering AI-ready data, packaged with clear definitions, embedded quality checks, and formalized access protocols. When paired with contracts, they create the predictability AI pipelines need to succeed.

Instead of spending weeks fixing broken integrations, teams can focus on innovation.

Of course, none of this happens in a vacuum. Most enterprise data infrastructures are complex, hybrid, and multi-cloud. Data products and contracts must work within that complexity, rather than ignoring it.

That means any successful approach must acknowledge what already exists. It must allow domains to define their own boundaries, respect existing platforms, and work incrementally toward decentralization.

It also means that no single tool will deliver this on its own. Instead, the focus should be on building the capabilities and conventions that allow teams to define, publish, and consume data products in a consistent way.

At Actian, we’ve built our Data Intelligence Platform with these ideas at its core. It enables domain teams to define and share data products through contracts, discover them in an enterprise marketplace, and manage quality through embedded observability.

It’s designed to scale, not by centralizing everything, but by enabling each domain to contribute to a shared ecosystem. Because we believe that decentralization isn’t chaos, it’s coordination through contracts.

Data products are how you scale your data strategy. Data contracts are how you make that scale sustainable.

Watch the 3-minute explainer video to learn more.

Come learn from Ole in person at Big Data Paris during his talk about ‘Metadata Management in the era of Artificial Intelligence’ on 02 October at 16h30 in Salle de conférence 2.