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What happens in the upper operational layer of data quality?

Turning data quality from a compliance obligation into something with commercial value. Laurens van der Drift argues that data quality is more than meeting requirements: it is about being able to act on what your data says. That shift changes which measures are worth taking and who should own them.

This is the practical view of the Metro model from Laurens van der Drift, whose experience comes from building data management software and from projects including government work. The conversation is full of examples and sharp observations about how organisations can deal with data more effectively.

Data quality as strategic value

The argument is that data quality is more than meeting compliance requirements. It is about being able to rely on what your data says when a decision depends on it. That reframing matters, because a measure justified only by an audit gets the budget an audit gets, and no more.

What that changes

• The owner of a data item becomes someone in the business, not in IT
• A quality rule is judged on whether it prevents a bad decision, not on whether it fills a report
• Improvement is continuous rather than a project with an end date

The practical side

The upper operational layer is where the checks and the tooling live: rules that run, results that get reported, and someone who acts on the result. Tools help here, but only after somebody has decided what right looks like.

Based on an episode of the Databewuster podcast, recorded in Dutch. The episode, the summary and the full transcript are on the podcast page. This English article describes what was discussed; it does not quote the guest directly, because the conversation was in Dutch.