Data redundancy
Data redundancy definition
Data redundancy is the unnecessary duplication of data. Whether it’s a massive database or a personal hard drive, data can be repeated for various reasons, including poor database design, data integration processes, or backup procedures. Although data redundancy is generally undesirable, data being held in a few separate places in the same data storage unit could be done intentionally to prevent data loss.
See also: data warehouse, data backup, database replication
History of data redundancy
Repetitive data has been an issue since the early days of data storage and management. The need for efficient and effective database design became obvious when businesses started generating large amounts of data. To solve this issue, Edgar F. Codd introduced the concept of normalization in the 1970s, meant to minimize data repetition.
Data redundancy advantages
- Redundant data can serve as a backup in case of data loss.
- Systems like RAID use data redundancy to ensure operations continue even if a hardware component fails.
Data redundancy disadvantages
- Storing redundant data requires more storage space, which costs businesses more.
- Updating the same data in multiple places is both time-consuming and a straight path to errors.
- If data is not updated uniformly, it could lead to data integrity issues.