Businesses rely on a library of customer data to stay competitive, whether your organization sells insurance, IT services or something else. That library gets new incoming data, and changes to existing data, constantly.
With multiple applications using this evolving data from multiple sources, deduplication becomes an essential tool against storage sprawl. Data centers define dedupe as a process to reduce storage demand by saving only one instance of a data point, rather than multiple copies for different systems to access separately. Deduplication lets disparate systems access that single data point.
An example will help define dedupe: Your company keeps a book of data about Customer ABC in its customer relationship management system's database. Customer ABC is also part of a pilot program for your company's new product, which means the same book of data exists in the development group's database for communicating about bugs, new releases and so on. You might also have a separate database used for financials that stores all the same information about Customer ABC. Dedupe means that the company can save just one book on Customer ABC, reducing the storage room required yet not losing any information from which it makes business decisions. The data center's IT systems maintain a reference path so that all three systems know where to find the book on this customer.
There are plenty of practical concerns with deduplication. It can be time consuming and expensive to sort through existing data to match up copies. For new data, storage systems must include the intelligence to synthesize information into one cohesive book; rather than writing a new one each time the company starts tracking a new parameter. But without dedupe, storage demands and complexity would thwart business initiatives like purchasing pattern analytics.