Reengineering and Migration -> Data migration

Reengineering and Migration > Data migration

It's not data that moves one from place to another, unless you think of places as being virtual.
Data migration is actually the translation of data from one format to another format or from one storage device to another storage device.
Data migration is necessary when a company upgrades its database or system software, either from one version to another or from one program to an entirely different program.

Software can be specifically written, using entire programs or just scripts, to facilitate data migration.
Another use of data migration is to store little-used data on magnetic tape or other backup storage methods.
This data may need to be stored for historical purposes or for periodic access.

Perhaps the most sensitive phase is validation and repair. In this phase, data is evaluated for potential problems, which are flagged and identified to the user.
Data migration typically has four phases: analysis of source data, extraction and transformation of data, validation and repair of data, and use of data in the new program. Perhaps the most sensitive phase is validation and repair. BMS Soft’s data migration solution decreases the risk and minimizes the errors inherent in data migration projects. At the same time, our data migration solution reduces the costs of data migration projects by automating processes, improving business-IT collaboration, and incorporating proven best practices.

BMS Soft’s three-part data migration solution includes:

   • Technology. The BMS Soft data migration solution supplies a comprehensive, open, and unified way to speed data migration and minimize errors.
   • Methodology. Drawing from practical experience, we provide a combination of best practices and techniques to make your data migration project successful. BMS Soft’s data migration solution offers a best-practice implementation methodology specifically designed for data migration projects.

Data migration typically has four phases:
1. Analysis of source data.
2. Extraction and transformation of data.
3. Validation and repair of data.
4. Use of data in the new program.

Perhaps the most sensitive phase is validation and repair.