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Data migration involves translating data from one format or storage device to another. It is necessary for system upgrades or archiving. The process typically involves four stages, including validation and repair. Migration software performs the necessary tasks, identifying and resolving potential issues.
Data migration means what it appears to mean: sort of. It’s not data that moves one from place to place, unless you think of places as virtual. It is actually the translation of data from one format to another format or from one storage device to another storage device. This also necessarily requires someone or something to translate. The data does not get up and go by itself to another format.
Data migration is required when a business upgrades its database or system software, either from one version to another or from one program to a completely different program. Software can be written specifically, using entire programs or just scripts, to facilitate the migration. Such updates or program changes may occur as a result of normal business practices or as a result of direction given following a corporate acquisition.
Another use of data migration is to archive lightly used data to magnetic tape or other backup storage methods. It may be necessary to keep this data for historical purposes or for periodic access. Individual computer users do this all the time when they back up their data to CD, DVD or external hard drives. Businesses large and small do this, of course, to protect and store their data. Migrated data typically moves offline but remains available through network access, leaving the online environment free to perform current activities.
Data migration typically has four stages: analyzing the source data, extracting and transforming the data, validating and repairing the data, and using the data in the new program. During each stage, the migration software works its electronic magic, performing the necessary machinations before moving the data through the process. Perhaps the trickiest phase is validation and repair. In this stage, the data is evaluated for potential issues, which are reported and identified to the user. At this stage, unsolvable issues can be identified, along with untranslatable data, so that they can be pushed aside and not clog up the entire data migration work.
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