What does data redundancy refer to?

Data redundancy refers to the duplication of data in multiple locations. This concept is important in data management because it can lead to issues such as inconsistency and potential confusion when multiple copies of the same data exist across different systems or databases. For example, if one system is updated but another is not, it can result in discrepancies that make it difficult to determine which data is accurate.

In database design, redundancy might be intentionally introduced for purposes such as backup, improving data retrieval speed, or ensuring data availability in different locations. However, it's equally important to manage redundancy effectively to avoid complications associated with data integrity and increased storage costs.

This understanding of redundancy highlights the need for careful planning in data architecture and management, emphasizing the balance between sufficient redundancy for resilience and the minimization of unnecessary duplication.