Which of the following best describes the concept of data integrity?

The concept of data integrity fundamentally revolves around the accuracy and reliability of data within a database. When data maintains its integrity, it means that the information is trustworthy, consistent, and correct over time. This is crucial for decision-making, as unreliable or inaccurate data can lead to flawed outcomes.

Data integrity encompasses several aspects, including how data is entered, stored, and maintained. Systems implement various constraints and checks to ensure that any data entered is valid and corresponds accurately to real-world values. This might involve establishing rules for data entry, such as formats, allowable values, and necessary relationships between data elements. Maintaining accuracy means that any updates or changes to data preserve its integrity and do not introduce errors.

In contrast, while consistency of data across different systems, completeness of data collected, and speed of data retrieval are all important aspects of data management, they do not specifically define data integrity. Consistency allows for reliable comparisons across systems, completeness ensures that necessary data points are present, and speed of retrieval pertains to performance measures rather than the quality of the data itself. Thus, accuracy and reliability over time best captures the essence of data integrity.