Data integrity refers to the overall completeness, accuracy, and consistency of data and processes during its entire lifecycle. Though this seems simple, the whole process of genuinely generating, maintaining, and transforming data with completeness and accuracy is a challenging task for any organization.
Data integrity addresses the “lifecycle of data.” This includes the steps involved in setting up and running analyses as well as managing the data that is collected, both raw chromatographic data but more importantly through the cycle of processing, interpreting, reviewing, reporting, and managing that data. So it is not only a concern about how to store data, as its generation through robust, modern, and innovative analytical experiments is equally as important.
