Guide · updated 2026-11-04
Clarifying questions to ask about messy data
The questions that prevent silent assumptions, grouped by topic.
Scope and grain
What does one row represent? Which period and population are in scope? What decision will the data support?
Values and rules
Which values count as missing? Is case meaningful? Which date and number formats are valid? What happens to invalid rows?
Ownership
Who decides when the data contradicts the dictionary? Who fixes the source?
Practise it
- Lesson: Profile before you change anything
- Exercise: Clean an order-line export