How can data redundancy be effectively managed in integration?

Managing data redundancy is a critical aspect of integration, and implementing data deduplication techniques is an effective way to address this issue. Data deduplication is the process of identifying and eliminating duplicate copies of data, which ensures that only unique instances of that data are stored. This not only reduces the amount of storage space needed but also improves data integrity and accessibility.

When data deduplication is in place, it simplifies data management by minimizing the amount of redundant data within the system. This approach is especially beneficial in environments where large volumes of data are processed, as it helps streamline data flows and enhances overall system performance. Moreover, deduplication facilitates better backup and recovery processes since it reduces the total data volume that needs to be managed.

The other strategies listed, while potentially useful in certain contexts, do not directly address the challenge of data redundancy in the same manner. Increasing data storage capacity simply means having more space to accommodate existing redundancies. Relying on cloud storage solutions can provide flexibility and scalability but does not inherently solve the redundancy issue without additional measures such as deduplication. Lastly, routinely archiving legacy data might help in managing outdated information but does not prevent or reduce redundancy in active data sets.

Thus, the focus on data dedup