Article · Data & AI
Data quality is a continuous capability, not a final step
Defining dimensions, measuring deviations, assigning ownership and tracking fixes creates a more reliable cycle for analytics and operations.
When quality is checked only at the end, the issue has already travelled through systems, reports and decisions. A continuous capability combines dimensions, measurement, ownership, prioritization and fix tracking so quality is not an isolated inspection.
Question for your context
Which quality dimensions are essential for data supporting a critical decision?
An idea that can shape the next decision.
Defining dimensions, measuring deviations, assigning ownership and tracking fixes creates a more reliable cycle for analytics and operations.
Connect each quality indicator to a concrete purpose.
Prioritize deviations by data impact and risk.
Create a feedback loop between consumers and producers.
Article · Data & AI
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