Which of the following is an advantage of data normalization?

Data normalization is a database design technique that organizes data to minimize redundancy and improve integrity. One of the primary advantages of data normalization is that it reduces data redundancy, which means it helps eliminate repetitive data entries across different tables. By structuring the data efficiently, related data can be consolidated, ensuring that information is stored only once. This not only saves storage space but also simplifies data management and maintenance, as updates need to be made in just one location rather than multiple instances.

This process also enhances the overall integrity and accuracy of the data, as it lowers the risk of inconsistencies that can arise from having duplicate records. As a result, when normalization is properly implemented, it leads to more reliable and manageable databases.

Other options presented may refer to various aspects of data management, but they do not capture the essential role of normalization in reducing redundancy. For instance, while improved data readability may be a benefit in some contexts, it is not a direct result of the normalization process itself. Similarly, increasing data import speed and eliminating the need for data cleansing do not represent key objectives of normalization, which fundamentally focuses on structuring the data effectively to reduce repetition and enhance data integrity.