Which of the following is NOT typically considered a data quality issue?

• A. Missing data
• B. Duplicates
• C. Outdated information
• D. Data encryption

Answer: (D)

Data quality concerns the accuracy, completeness, consistency, and timeliness of information. Missing data reduces completeness because there are gaps where values should be, making it hard to rely on the dataset. Duplicates cause redundancy and can distort results, harming consistency and accuracy since the same fact appears more than once. Outdated information undermines timeliness and relevance, leading to decisions based on facts that are no longer valid. Data encryption, by contrast, is a security measure that protects confidentiality by scrambling data so unauthorized users can’t read it. It doesn’t describe a flaw in the data itself and doesn’t directly impact the information’s accuracy, completeness, or timeliness. So encryption is not typically considered a data quality issue.