Data restoration is the process of copying backup data from a secondary storage location and restoring it to its original or a new destination.
It is essential for retrieving lost, damaged, or stolen data and making it usable again. Examples of data restoration include restoring a database to its previous state after an accidental deletion or transferring files to a new server during an infrastructure upgrade. The data restoration techniques depend on the data type and the backup method.
While data recovery and restoration aim to retrieve lost data, they are distinct processes with different methods. Data recovery focuses on retrieving some or all lost files from a backup or damaged media, typically after accidental deletion or corruption.
On the other hand, data restoration involves restoring a complete backup image from a backup system. This backup image is an exact copy of everything stored on a computer or device at a specific point in time.
Because it restores the entire system or dataset, data restoration is often a more reliable solution when dealing with data loss, ensuring that all files present at the time of the backup are fully recovered.
Data restoration is essential to data management, requiring reliable backup copies from traditional backups, snapshots, or continuous data protection (CDP).
The method for restoring data depends on the type, extent, and cause of the data loss, as well as the backup method used.
Selecting the appropriate data restoration method minimizes downtime and ensures business continuity. Whether opting for instant recovery for immediate access, continuous data protection for precise recovery points, or traditional and cloud-based backups for larger recovery needs, the right choice depends on your organization's specific requirements and infrastructure.
Recovering lost or outdated datasets can disrupt analysis if not properly versioned or governed. With OWOX Data Marts, every transformation and data update is tracked, allowing you to restore previous versions of datasets instantly when needed. This version-controlled approach ensures data accuracy, continuity, and compliance across all reporting layers.