Data protection seeks to balance several divergent, yet business critical objectives simultaneously. A well designed, implemented and managed data protection system will employ many different technologies and processes that, together, allow a business to:
- Comply with internal policies and external regulations
- Promote operational efficiency
- Ensure business continuance in the event of a disaster, and
- Minimize both operational and capital expenditures
The evolution of existing technologies like tape and hard drives and the introduction of new technologies like, most recently deduplication, force businesses to re-evaluate their data protection plans on a two to three year cycle. This is because data continues to grow at an increasing rate. Technological improvements, like hard drives with twice the capacity for the same price; and tapes with twice the density and 50% more throughput, for example, can dramatically impact a business' ability to deal with additional data.
Data is backed up for use in one or more of the following ways:
This includes any use that can reasonably be expected to happen. Examples of operational use include restoring a deleted file, recovering from the failure of a single system, and providing a developer with a copy of a production database. The need to minimize effort and delay; and maximize efficiency dominates here.
Although these use scenarios are not likely to happen, if one was to happen, the impact on the business would be so great that the cost of protecting against the remote chance is justified.
This data is not likely to be used, but preservation of this data for a predetermined amount of time is mandated by company policy, external regulations or both. The consequences of non-compliance validate these expenses.
Each significant data set will have requirements in at least one of these areas. It is critical to understand each data set and document its business requirements for the following reasons:
- to map requirements to technologies and processes
- to understand future growth requirements
- as a basis for reporting on data protection activities, and
- to obtain executive sponsorship for data