Reliant - Contain Capacity Demands

Experts have indicated that one of the leading causes of data storage capacity demand that businesses are facing on a daily basis is data growth. More specifically, data growth is directly contributing to capacity demand to the tune of between 40 percent and 650 percent on an annual basis. Storage capacity now accounts for between 33 cents and 70 cents out of every dollar that businesses are spending on IT-related hardware, which represents a huge cost of doing business that can no longer be ignored. If your organization is currently struggling with how to contain capacity demands, there are a few key things you should consider.

Avoid Wasted Resources

Wasted resources are among the leading contributors to capacity demands, which in turn represents a huge amount of wasted money that businesses can no longer afford. Look at not the quantity of what you're storing but the quality - get rid of duplicates, orphan data, information that is rarely utilized and more to save as much space as possible and decrease waste.

Deduplication and Compression

Another way to help contain storage capacity demands has to do with deduplication and compression. Though these are designed primarily to be short-term fixes, as the old saying goes - "every little bit helps." Deduplication is a process that is designed to eliminate copies of data that are either no longer needed or were never needed in the first place - the type of copies that are contributing to wasted resources. Compression is a practice that takes a specific amount of data and essentially makes it smaller, allowing you to store the same amount of information in less space.

Data Lifecycle Management

Another important element of managing capacity demands has to do with data lifecycle management, which is also commonly referred to as information lifecycle management. By creating the types of policies that automate where data is moving and how it's getting there now, you can save your organization a great deal of time, money and energy in the future. For example, you may flag data created by a specific department within your organization to always be stored in the same basic space. This allows professionals to control the ways in which specific arrays are being utilized.