What does data integrity refer to?

Data integrity specifically pertains to the accuracy and consistency of data throughout its lifecycle. This concept ensures that data remains reliable and trustworthy from the moment it is created, through its modification, and until its eventual deletion. Maintaining data integrity involves implementing practices that prevent corruption, unauthorized access, and unintentional changes to data, ensuring that it is both correct and complete.

Data integrity is critical in various fields, particularly in databases and information systems, where dependable data is essential for making informed decisions, conducting analyses, and maintaining compliance with regulations. By focusing on accuracy and consistency, organizations can achieve better data quality, which directly influences operational efficiency and decision-making processes.

In contrast, other options like the variety of data or the number of storage platforms do not address the core aspect of data integrity, which hinges on how reliably the data represents the true values and is preserved over time. Similarly, while speed of data processing is relevant to performance, it does not relate to the integrity or trustworthiness of the data itself.