Which statement best distinguishes data integrity from data reliability?

• A. Data integrity concerns correctness after processing; data reliability concerns consistency across repeated collections
• B. Data integrity concerns security; data reliability concerns formatting
• C. Data integrity concerns speed; data reliability concerns storage
• D. Data integrity concerns access controls; data reliability concerns encryption

Answer: (A)

Data integrity is about the accuracy and trustworthiness of data as it moves through systems. It focuses on correctness after processing, ensuring the data hasn’t been corrupted or altered during capture, transmission, storage, or computation. Data reliability, on the other hand, is about consistency of data over time and across repeated measurements or collections; if you gather the same data under the same conditions, you should obtain similar results.

So the best statement captures that integrity centers on correctness after processing, while reliability centers on consistency across repeated data collections. For example, a lab result must remain accurate after processing (integrity), and if you repeat the measurement under the same conditions, you should get the same result each time (reliability).

The other options mix in aspects like security, formatting, speed, or access controls, which relate to protecting data or system performance rather than the distinct ideas of data integrity and data reliability.