In what scenario would data redundancy be seen as detrimental?

Data redundancy is often considered detrimental primarily because it can lead to data inconsistencies. When the same data is stored in multiple locations, there is a risk that updates to the data may not occur uniformly across all instances. For example, if a customer's address is stored in two separate databases and is updated in one but not the other, this creates discrepancies in the information recorded. Such inconsistencies can lead to incorrect conclusions being drawn, errors in reporting, and a loss of trust in the data managed by the organization.

In contrast, scenarios that involve backing up data, enhancing security, or facilitating easy access typically offer beneficial outcomes related to redundancy. Backups ensure data safety in case of loss, enhancing security involves creating copies of sensitive information to protect it, and facilitating access can involve maintaining multiple copies for performance reasons. These scenarios showcase how redundancy can be useful, but when it results in conflicting data, it poses a significant challenge to effective data management.