A data quality framework the whole organisation could see
Over 1,500 accumulated business rules reviewed and rebuilt into a governed framework, with a Power BI dashboard that made data quality visible to the teams responsible for it.
A council of this size runs data quality as a by-product of a dozen systems rather than as a discipline of its own. Rules had been added over years, each sensible when written, but the set as a whole had never been reviewed against itself — more than 1,500 of them by the time the work started.
The practical cost was not a broken report. It was that nobody could answer what "good" meant for a given dataset without asking the person who had last touched it, and that data dictionaries and integration maps were treated as documentation to be produced for an audit rather than as an operational asset.
- Reviewed the full body of over 1,500 business rules, establishing what each rule was actually asserting and where rules contradicted or duplicated one another.
- Rebuilt the data dictionaries and system integration maps as maintained artefacts, so the definition of a field and the path it travels are answerable without tribal knowledge.
- Built a Power BI dashboard reporting quality against the framework, aimed at the business owners of each dataset rather than at the digital team.
- Aligned the framework with the organisation’s data protection and compliance obligations, and with existing solution architecture standards.
- Data quality issues reduced by 7% across the reporting scope.
- Data visibility improved — quality became something teams could see for their own data instead of a periodic report about them.
- Dictionaries and integration maps moved from stale documentation to maintained reference.
Have something like this sitting on your desk?
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