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Data purging is the process of permanently removing obsolete data from a specific storage location when it is no longer required.
Common criteria for data purges include the advanced age of the data or the type of data in question. When a copy of the purged data is saved in another storage location, the copy is referred to as an archive.
The purging process allows an administrator to permanently remove data from its primary storage location, yet still retrieve and restore the data from the archive copy should there ever be a need. In contrast, the delete process also removes data permanently from a storage location, but doesn’t keep a backup.
In enterprise IT, the compound term purging and archiving is used to describe the removal of large amounts of data, while the term delete is used to refer to the permanent removal of small, insignificant amounts of data. In this context, the term deletion is often associated with data quality and data hygiene, whereas the term purging is associated with freeing up storage space for other uses.
Strategies for data purging are often based on specific industry and legal requirements. When carried out automatically through business rules, purging policies can help an organization run more efficiently and reduce the total cost of data storage both on-premises and in the cloud.
Techopedia Explains Data Purging
Many database management tools include automatic purging features. For example, some Microsoft products support an automatic purge technique that uses a circular buffer methodology, in which older data is automatically purged to make way for newer data. In other cases, administrators must manually purge data from the database.
Setting up data purging solutions can raise questions for developers, database administrators and others with these kinds of responsibilities. Issues involved in setting up data purging methods include questions about server operation and client access during the data purging process. Other questions involve how to access the right data purging tools or how to plan practices for a specific technology such as a database.
