Which statement best defines data integrity in business information systems?

Which statement best defines data integrity in business information systems?

• A. The accuracy and consistency of data over its lifecycle
• B. The speed at which data can be retrieved
• C. The physical security of servers
• D. The visual presentation of data

Answer: (A)

Data integrity is about keeping data accurate and consistent as it moves through its lifecycle in a business information system. It matters because information goes through many steps—collection, processing, storage, and retrieval—and any corruption or unauthorized modification can lead to faulty decisions. Maintaining data integrity means using validation rules at input, enforcing constraints that preserve relationships between data, and using mechanisms like audit trails, checksums, and version control to detect and correct errors. When data stays accurate and consistent, reports and analyses reflect reality and support trustworthy outcomes. The other aspects mentioned—how fast data can be retrieved, the physical security of servers, or how data is presented visually—are important but describe performance, protection, or presentation, not the trustworthiness of the data itself. Therefore, focusing on accuracy and consistency over the data’s lifecycle best defines data integrity.

Data integrity is about keeping data accurate and consistent as it moves through its lifecycle in a business information system. It matters because information goes through many steps—collection, processing, storage, and retrieval—and any corruption or unauthorized modification can lead to faulty decisions. Maintaining data integrity means using validation rules at input, enforcing constraints that preserve relationships between data, and using mechanisms like audit trails, checksums, and version control to detect and correct errors. When data stays accurate and consistent, reports and analyses reflect reality and support trustworthy outcomes. The other aspects mentioned—how fast data can be retrieved, the physical security of servers, or how data is presented visually—are important but describe performance, protection, or presentation, not the trustworthiness of the data itself. Therefore, focusing on accuracy and consistency over the data’s lifecycle best defines data integrity.