Data Products

What it is

What makes data a product is the management around it, not the data. Someone is accountable, the consumers are known, the quality is stated and the terms of use are written down.

There is now a shared vocabulary. The Open Data Product Standard, version 1.0.0, was announced on 2 October 2025 and provides a shared vocabulary for describing what a data product is. It is aligned with the Open Data Contract Standard and governed under the Linux Foundation. DII read the announcement, not the standard.

Why it matters

A vendor-neutral standard for describing data products reached version 1.0 in October 2025 under the Linux Foundation, aligned with the open data contract standard. Shared vocabulary makes the idea easier to adopt.

One survey, reported by its sponsor, says operational use of data products rose from 48% of surveyed organisations in 2024 to 69% in 2026. The survey is vendor-sponsored and its respondents chose to answer a survey about data products, so the figures overstate practice at large.

The problem it addresses

DII editorial view

Data delivered on request, project by project, has no owner once the project ends. Consumers cannot tell what is maintained, what quality to expect or whom to ask. A data product makes those things explicit and keeps them true over time.

Business and organisational relevance

DII editorial view

The shift is from delivering data on request to offering it as something maintained. That needs funding and ownership that outlast a project, which is why a study of implementations reports difficulty with shifting responsibility for data products.

Practical use cases

• A small number of well-used datasets given an owner, a contract and quality measures
• A catalogue of data that consumers can find and rely on
• The unit of ownership in a data mesh

Benefits and opportunities

• Consumers know what they can rely on and who to ask
• Reuse, because the data is maintained for more than one use

Risks, limitations and dependencies

• Relabelling existing datasets as products without changing who maintains them
• Products with no clear consumers
• Ownership that ends when the project that built the product ends

Prerequisites for adoption

DII editorial view

• Known consumers; a product nobody uses is not a product
• An owner whose responsibility outlasts the project that built it
• Funding for maintenance, not only for delivery

Implementation considerations

• Start with clear consumers. Begin with a few data products that people already depend on.
• Describe each one fully. Give each an owner, a contract and quality measures.
• Fund them to last. A product needs maintenance after it is built; decide who pays.

The DII Radar assessment

Approved DII Radar assessment

DII assesses Data Products as High relevance, with direction Rising. Its strategic impact is assessed as High and its enterprise adoption as Scaling. It is one of the ten entries on the current Radar.

DII relevance is our assessment of current significance and momentum, based on evidence, market development and adoption. Direction is the observed trajectory of relevance and adoption. Strategic impact is the potential or current significance to enterprise data capability, and enterprise adoption is the extent of current real-world enterprise adoption; together they set the position on the Radar. The Radar is not a prediction, vendor comparison or performance ranking.

Evidence basis: Bitol (Linux Foundation) Open Data Product Standard v1.0.0, 2 October 2025; BARC survey 2026, sponsored by Actian (operational use 48% in 2024, 69% in 2026).

See Data Products on the Radar →

What to consider next

DII editorial view

• Start with a few data products that have clear consumers
• Describe each with an owner, a contract and quality measures
• Decide who pays to keep each one running