Unified Communications Research Library

Data and information management continue to be a major problem in enterprise organizations that no one likes to think about. So when a new technology like data deduplication comes along that promises to solve today's backup problems, it is no surprise that organizations may view data deduplication as some kind of silver bullet that will provide a quick fix to their data protection issues. Unfortunately the dilemma that organizations find themselves in is that they are unclear as to how it will benefit them, what exactly data deduplication does, what ways it is implemented and what problems it can and should solve in their storage and backup infrastructure.

To clarify some of the confusion surrounding data deduplication, organizations need to understand how it works as well as what problems it solves and what options are available. To do that, they need to understand:

• The main benefits driving the adoption of data deduplication today and what business and technical problems it addresses in organizations
• The primary role of data deduplication to reduce the size of data stores (primary, archive and backup) while improving the backup and recovery experience
• The different ways in which data deduplication is implemented and under what circumstances each form of data deduplication is the right fit
• Enterprise organizations may need to obtain and then manage the multiple ways in which data deduplication is implemented

  To achieve this last objective enterprise organizations need to consider the software that is part of Symantec's information management suite. It provides solutions that address these different needs around data deduplication so organizations do not have to guess the best form of data deduplication for them, but can instead focus on deploying solutions that meet the specific needs of their different applications or business units within their organization.

  Read this white paper to learn how Symantec software allows customers to put deduplication technology as close to the source of data as possible.