How can organizations mitigate the impacts of data redundancy?

Organizations can mitigate the impacts of data redundancy primarily through the use of data normalization techniques. Data normalization is a systematic approach to organizing data in a database to reduce redundancy and improve data integrity. This involves structuring a database in such a way that each piece of information is stored only once, which helps in eliminating duplicate data entries.

When normalization is applied, it identifies and removes duplicate data through a process of dividing large tables into smaller, interconnected tables, ensuring that each table has a specific purpose and primary key. This results in a streamlined database structure that not only saves storage space but also enhances consistency by ensuring that any update to data only needs to occur in one place.

Normalization further propagates efficiency when it comes to data management because it simplifies the insertion, deletion, and updating of records. By adhering to normalization principles, an organization can significantly reduce data redundancy, leading to overall improved database performance and reduced chances of data anomalies or errors.

Other options, while they may contribute to data management in various ways, do not specifically address the reduction of data redundancy as effectively as normalization techniques. For example, regularly archiving data pertains more to data management and retention strategies rather than addressing redundancy directly. Expanding database capacities and using more complex data types could lead to more