Data Governance & Quality
Trusting the numbers
Rules and checks that catch bad data on the way in, and a clear answer to who owns which figure and where it came from.
Selected work demonstrating this service.
- Designed a comprehensive infrastructure framework for DTU impacting 14 departments, featuring flexible modules, unified data pipelines, and structured support strategies for long‑term adoption.
- Gathered and analyzed business requirements to translate into actionable features and user stories aligned with data governance standards.
- Wrote a scope rule into the repository after a restructure carried another company's inventory, firewall allowances and prose into it — and kept the quarantined residue under the secret scanner rather than excluding it.
- Wrote tests for the checkers themselves after establishing that a checker fed only clean input will one day report clean because it read nothing — planting a misspelling to confirm the spell‑check finds it, and taking an id range from the database rather than from a number in the test.
- Built a cross‑language content check that fails when a translation drops a figure the English states, and when a language uses notation it does not use — finding two Danish descriptions missing a metric and sixteen Ukrainian spans quoting in the English style.