Explain the term "data culling."

Data culling refers to the process of filtering out non-relevant data before review. This procedure is particularly important in contexts like legal discovery or data management, where an overwhelming amount of information exists, making it essential to focus on what is pertinent to the task at hand.

By implementing data culling, organizations can streamline their processes, reduce costs, and enhance efficiency by concentrating only on the information that is relevant to their objectives. This targeted approach helps ensure that time and resources are not wasted on analyzing or reviewing data that doesn’t contribute to the decision-making process or the specific inquiry in question.

In contrast, the other options represent different concepts related to data management but do not capture the essence of data culling. Data storage, archiving, and merging datasets serve distinct purposes and do not involve the selective filtering process inherent in culling.