Data Reduction without Data Loss

Any lack of efficiency is reason enough for improving, and the success of any changes comes down to getting the results you expect while saving time, money and effort. Due to the constant amount of uploading, downloading, sharing and commenting taking place online, a tremendous amount of data is being generated every day. Businesses of every industry are finding themselves as part of this ever-growing ocean of data and they’re accumulating large amounts to sort through to decide what’s valuable.

Data Reduction without Data LossEven after an organization or department has identified what should be stored, there’s still the matter of how to store everything. Maximizing the storage space your business has is the ultimate aim, allowing you to preserve everything without blowing your budget.

Data reduction is the key to achieving this maximization, yet it isn’t just about scaling down a company’s storage needs; it’s about reducing costs related to energy, cooling and how extensive your storage system is. Being able to gain new storage efficiencies entails looking at your company’s requirements and finding the right method (or methods) for optimizing your storage infrastructure.

The types of data reduction

A few data reduction methods have proven to be the most effective, and you can use more than one at a time as part of a reduction strategy:

  • Compression: Here data is reduced by removing either unnecessary or redundant information to reduce the amount of bits required to store the file. Compression can occur as either lossless or lossy compression. Lossless means just what is says; no information is lost and when you access the file, it will be the same as the original file, which is best for text or data files. Lossy means that some data is lost after compression. This method is common for photos, video or audio files.
  • Deduplication: This technique is a straightforward, commonsense one. Deduplication prevents any redundancies in the data being stored, and eliminates any reoccurring data. Rather than including multiple attachments of the exact same file, the system keeps only one copy. You can also do this on a file level or by breaking files into different parts and running them through an algorithm to avoid any redundancies within those separate parts. Deduplication is becoming common enough it soon may be an established part of storage methods.
  • Thin provisioning: This approach aims at maximizing the storage space available without setting hard limits on the space an individual server can use. Essentially, you tell each server that it can use a set amount of space, even if the total space provided for all servers is more than the total space available. Because a server requests more space than it actually uses, your storage host will “lie” to it, telling it that it has as much space as it has requested while actually reserving only what the server is currently using. Thin provisioning also allows a certain degree of scalability, in that you can add more storage volumes if your storage unit beings reaching capacity.

Optimizing storage and saving expenses

With these reduction techniques, you can continue amassing information without worrying about running out of space. If you don’t want to deal with setting up and maintaining advanced data reduction technology, you can find an enterprise storage array with the functionality built in.

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