Before deduplication platforms could emerge, data was manually checked for errors. It was humanly impossible to maintain an error-free database even after multiple checks. But with the help of most modern technological advancements, it is now easy to maintain error-free databases. At its simplest definition, data deduplication refers to the process of eliminating redundant or outdated data from a data set. In the process of deduplication, extra copies of the same data are deleted, leaving only one copy in the database. Data is analyzed to identify duplicate byte patterns to ensure the single instance is indeed the single file. Then, duplicates are replaced with a reference that points to the stored chunk.
Evolution of Data Deduplication:
By the early 2000’s, business data was moving global, real-time, and mobile. IT teams were challenged to backup and protect massive volumes of corporate data across a range of endpoints and locations with increased efficiency and scale. Various applications were developed, which analyzes data at the file object level to identify file duplicates in attachments, emails, or even down to the folder from which they originate. This approach added significant gains in accuracy and performance for data backups, lowering the barrier for companies to efficiently managing and protecting large volumes of data.
A simple example:
Let us now, for example, consider an email server that contains 100 instances of the same file attachment of 1 MB; say, a campaign template containing graphics, which was sent to everyone on the marketing staff. Without data duplication, if everyone backs up his/her E-Mail inbox, all 100 instances of the template are saved; requiring 100 MB storage space. With data deduplication, only one instance of the attachment is actually stored; each subsequent instance is just referenced back to the one copy that is already saved, reducing storage and bandwidth demand to only 1 MB.