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Data reduction primarily focuses on minimizing the amount of data that needs to be stored or transmitted while retaining essential information. The aim is to achieve greater cost savings and efficiency. By shrinking data capacity, organizations can reduce the storage space required, lower associated costs, and improve data processing speeds. This is particularly important in environments where large volumes of data are generated, making it crucial to manage, store, and analyze data efficiently.

While the options that suggest increasing redundancy, enhancing the quality of data, or merely storing more data efficiently touch on related concepts, they do not align with the core goal of data reduction. The concept fundamentally revolves around reducing data volume to optimize resources and improve overall performance.