How is data integrity best defined?

Data integrity refers to the accuracy, consistency, and reliability of data throughout its lifecycle. It is vital for ensuring that the information stored in databases and systems remains correct and trustworthy. When data integrity is maintained, users can have confidence that the data reflects the real-world scenarios it represents, which is crucial for making informed decisions based on that data.

This concept encompasses various practices, including validation checks, error detection mechanisms, and regular audits to ensure that data remains unaltered and valid over time. Thus, ensuring data is accurate and reliable is the central focus of data integrity. The other options may play a role in the overall data management process but do not directly define data integrity itself. For example, while backing up data regularly is essential for data recovery, it does not inherently relate to the accuracy or reliability of the information contained within that data.