Data & consent · Working definition
Dirty data
What is dirty data?
In data-quality work, dirty data is inaccurate, incomplete, duplicated, inconsistent, or outdated. Responsible data use also requires an established source, permitted uses, and permission history. Poor quality and unclear permission create different problems, and both deserve attention.
Dirty data: an illustrative example
A sales team buys a contact list with duplicate records, invalid addresses, and outdated job titles. The list also lacks a clear permission history, so the team cannot assume it is suitable for a campaign.
Sources and related reading
- Clean Data Alliance: The Weather of Data — related reading
This is a practical working definition. Examples illustrate the concept; they are not verified client results. Working definitions and accountability lenses are not claims of a universal standard or original coinage.
Related data & consent terms
- Clean data
Clean data combines quality with responsible use: accurate and verified where possible, collected for a clear purpose, used with appropriate permission, and maintained over time. Personal information is protected, and anonymous information is used where appropriate. A smaller, reliable audience can be more useful than a large list of suspect contacts.
- The Clean Data Imperative
The principle that organizations should verify data quality, establish permission and purpose, and maintain the information used for decisions. Unverified records, decaying contacts, and bot-inflated activity are infrastructure problems that require better systems and ownership.
- Access control
Rules and technical measures restricting who can use information or systems.
- AI disclosure
Clear information about material AI involvement in a service or communication.