Why is "data redundancy" avoided in Relativity?

Avoiding data redundancy in Relativity is primarily focused on ensuring efficient data management and minimizing storage costs. When data is redundant, it means that the same information is stored in multiple places, which can lead to issues such as increased storage requirements, higher costs for managing that data, and complications in maintaining data integrity.

Efficient data management is critical in a system like Relativity, where a large amount of data is often processed for legal and investigative purposes. By minimizing redundancy, the platform can streamline data operations, reduce the risk of errors, and implement more effective data governance practices. This not only translates to saving costs associated with storage but also enhances the overall performance of the system by allowing it to focus on managing unique data efficiently.

The other factors, while important in their own rights, do not capture the primary reason for avoiding data redundancy in the same way. For instance, while data accessibility and retrieval speed are essential, they are more indirect benefits of maintaining an efficient data management strategy that reduces redundancy. Increasing system downtime is contrary to the goals of effective data management, as it would negatively impact performance and accessibility.