What does the term "data integrity" imply?

The term "data integrity" fundamentally refers to the accuracy, consistency, and reliability of data throughout its lifecycle. When data integrity is maintained, it ensures that the information is correct, trustworthy, and represents the real-world scenarios it is intended to reflect. This reliability is crucial for decision-making processes, as decisions based on inaccurate or inconsistent data can lead to errors and undesired outcomes.

While other options touch on different aspects of data management, they do not capture the essence of data integrity. For instance, data being affordable to store speaks to cost considerations rather than the quality or accuracy of the data itself. The ability to easily retrieve data focuses more on accessibility and organization, which are separate from the integrity of the data. Lastly, stating that data is complex and hard to understand does not relate to its integrity; in fact, integrity can exist in both straightforward and complex datasets. Therefore, the notion that data should be consistent and accurate is the core principle of data integrity.