Data quality assessment

From Wikipedia, the free encyclopedia
Jump to: navigation, search

Data quality assessment is the process of exposing technical and business data issues in order to plan data cleansing and data enrichment strategies. Technical quality issues are generally easy to discover and correct, such as:

  • Inconsistent standards in structure, format/ values
  • Missing data, default values
  • Spelling errors, data in wrong fields

Business quality issues are more subjective and are associated with business processes such as generating accurate reports, ensuring that data driven processes are working correctly.

Business data quality measures like accuracy and correctness are subjective and need Subject Matter Expert (SME) involvement to assess data quality.


  • Feeney, Griffith. Data Assessment. In: Paul Demeny and Geoffrey McNicoll (Eds.). 2003. The Encyclopedia of Population. New York, Macmillan Reference USA, vol.1, 190-193