Topic starter
23/06/2026 7:20 pm
TL;DR: Data teams are treating data as a reusable product with named owners, consumer definitions, quality SLAs and lifecycle management because traditional pipeline-first models keep producing distrust and rework, according to Collibra. The governance shift matters because trust becomes an asset property, not a downstream validation exercise.
Editorial analysis by NHI Mgmt Group, based on content published by Collibra: “Data as a product: How leading organizations are rethinking their data strategy”.
Key questions
Q: How should organisations implement data-as-a-product in governance programmes?
A: Start by assigning named ownership to the data asset, not just the pipeline, then define consumers, quality expectations and lifecycle state.
Q: Why does data-as-a-product reduce trust problems in analytics?
A: It reduces trust problems because it replaces ambiguous stewardship with explicit ownership, quality standards and consumer commitments.
Q: What breaks when data has no named owner?
A: Quality becomes nobody’s job, definitions drift and consumers create shadow workarounds such as spreadsheets and local extracts.
Practitioner guidance
- Define named data product owners Assign accountable owners to critical data assets, with responsibility for quality, availability, consumer definition and lifecycle decisions.
- Publish data contracts for governed datasets Document format, freshness, completeness and ownership expectations for datasets that feed reporting, analytics or operational decisions.
- Expose certification and lineage in discovery Make provenance, ownership and quality status visible before consumers request or use a data product.
Bottom line: The article frames data quality as an ownership problem, not a tooling problem.
Explore further
View Full Forum → | NHI Foundation Course → | Our Services → | Read the full analysis →
25/06/2026 3:17 am
Data-as-a-product is really an accountability model, not a catalog feature. The article makes clear that pipeline-first thinking leaves ownership diffuse and quality reactive. When no one owns the asset, no one owns the trust failure either. The practitioner lesson is that governance must bind to the data product itself, not just the infrastructure that moves it.
A question worth separating out:
Q: How is a data marketplace different from a data catalog?
A: A catalog helps users find and understand data, while a marketplace adds the operational layer for requesting access, evaluating trust signals and using certified data products at scale. In practice, the marketplace is where governance becomes consumable, because ownership, quality and access paths are presented as part of the asset.
👉 Read our full editorial: Data as a product redefines trust, ownership and governance