I'm the administrator of a network server system with 13 workstations in a law firm. I would like to know how often I should perform backups over a one month period.
First of all, congratulations on your decision to implement a backup strategy for your data. Disaster recovery can quickly fall to the bottom of a busy IT person's list of priorities until it's too late -- you are to be commended for your foresight.
There have been volumes of material written on developing a viable backup plan -- run a search on any of the TechTarget offerings if you don't believe me! Let me offer a few ideas to get you started.
"What is a good approach in terms of complete vs. partial backups vs. time required for each?" Rather than re-invent the wheel, I will quote one of the ATE team members from searchstorage.com, Jim Booth:
"As a backup practice, both incremental and differential backups accomplish the same thing: they allow you to reduce the resources needed to backup data. But how they accomplish this task is different. If archive bits are cleared after each backup, this is called an "incremental" backup. If the archive bits are cleared only after a full backup, then this is a "differential" backup.
An incremental backup clears the archive bits each time data is backed up. This means that each backup will be small. To perform a restore, a copy of the last full backup and each incremental will have to be restored to get all files to their last known state. In most cases, a full backup will be performed weekly while an incremental backup is performed daily.
A differential backup clears archive bits only after a full backup. This means that daily backups get gradually larger -- but restore is easier. A full restore only requires the last full backup and the last differential. Incremental backup allows for a more granular restore, but differential backups are typically easier to restore."
This should give you a place to start your research in this matter. Searchstorage.com can provide more reference material and information, as well as a generic search engine query.
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