10 Data Quality Assessment Tips:

1. Data are outdated as soon as they enter the database
2. Data conversion is a major source of DQ problems
3. Convincing the CEO a DQ problem exists is a challenge (and a must)
4. DQ assessment needs to be grounded in (financial) numbers
5. Establish DQ benchmarks across the company
6. Consider doing both objective and subjective DQ assessment
7. Manual reconfirmation is the royal road (to DQ)
8. Selecting validation samples is tricky business
9. Data redundancy drives quality
10. Ad hoc databases are priceless

Link to External Resource: Tom’s Ten Data Tips

Source: Tom Breur, XLNT Consulting

See more Resources like this one in this Data Quality Resource Guide Section: Data Quality Best Practices