C.5 · Data Engineering & Analytics
Data Governance, Quality & Privacy
Lineage, quality gates, and a catalogue people actually use
What we build
Governance that makes data usable rather than merely documented. A catalogue populated automatically from the platform, column-level lineage end to end, data quality tests that fail a pipeline before a dashboard lies, ownership assigned to a person rather than a department, classification and masking for personal and regulated data, retention enforced by the platform, and subject access requests answerable without a manual search.
Capabilities
- A catalogue populated from the platform itself, so it does not go stale in a month
- Column-level lineage from a report back to the source column that produced it
- Quality tests that block a pipeline rather than annotate a wrong result
- Classification, masking, and tokenisation applied to personal and regulated data
- Retention and deletion enforced by the platform, on a schedule you can evidence
- Subject access and erasure requests answerable from the catalogue, not by hand
Related services
How it connects
Where it sits in the stack.
This service, and the two it hands off to. None of them can be optimised alone.
Data Governance
Governance that makes data usable rather than merely documented.
Data Platforms
Data platforms built for freshness and lineage.
Data Engineering & Analytics · see serviceBusiness Intelligence
Reporting that a leadership team can actually argue from.
Data Engineering & Analytics · see serviceBring us the whole problem.
Tell us where the work is stuck, whether that is a model that never reached production, an application nobody can change, a data platform nobody trusts, or a plant the business cannot see. An engineer replies with a first read, not a sales deck.