What type of backup method reduces data redundancy by only backing up files that have changed?

What type of backup method reduces data redundancy by only backing up files that have changed?

• A. Full backups
• B. Incremental backups
• C. Differential backups
• D. Mirror backups

Answer: (C)

The correct answer is incremental backups. This type of backup focuses on efficiency by only saving changes made since the last backup was performed, whether it was a full backup or the previous incremental backup. By doing this, incremental backups significantly reduce the amount of data redundancy compared to full backups, which save an entire dataset each time, and differential backups, which save all changes made since the last full backup. Incremental backups are particularly advantageous for organizations that need to optimize storage space and minimize backup time, as they only capture new or modified data. This method not only saves time during the backup process but also makes restoring data more efficient, as it involves backing up fewer data points over successive intervals. This practical approach makes incremental backups a popular choice in various data management strategies.

The correct answer is incremental backups. This type of backup focuses on efficiency by only saving changes made since the last backup was performed, whether it was a full backup or the previous incremental backup. By doing this, incremental backups significantly reduce the amount of data redundancy compared to full backups, which save an entire dataset each time, and differential backups, which save all changes made since the last full backup.

Incremental backups are particularly advantageous for organizations that need to optimize storage space and minimize backup time, as they only capture new or modified data. This method not only saves time during the backup process but also makes restoring data more efficient, as it involves backing up fewer data points over successive intervals. This practical approach makes incremental backups a popular choice in various data management strategies.