Which of the following is an indicator of data integrity?

Data integrity refers to the accuracy, consistency, and reliability of data over its lifecycle. It ensures that data remains trustworthy, which is essential for effective decision-making and operations in any organization.

When considering the indicator of data integrity, the suggestion that data is identical during transfer is particularly significant. This means that when data is transmitted from one location to another, whether it’s between databases, networks, or systems, it should retain its original state without any alterations. Maintaining this condition demonstrates that the data has not been corrupted, tampered with, or lost during the transfer process, thereby confirming its integrity.

In contrast, frequently modifying data does not inherently indicate that the data is accurate or consistent; rather, it can introduce risks of errors or inconsistencies if not managed properly. Visualization in reports offers insights into data, but it does not validate the integrity of the data itself. Lastly, manually entering data into databases can raise concerns about errors and inconsistencies, which can adversely affect data integrity if not carefully controlled. Thus, the notion of ensuring that data remains identical during transfer is a fundamental principle that directly correlates with maintaining data integrity.