Data migration is the process of transferring data between storage types, formats, or computer systems. Data migration is usually performed programmatically to achieve an automated migration, freeing up human resources from tedious tasks. It is required when organizations or individuals change computer systems or upgrade to new systems, or when systems merge (such as when the organizations that use them undergo a merger/takeover).

To achieve an effective data migration procedure, data on the old system is mapped to the new system providing a design for data extraction and data loading. The design relates old data formats to the new system's formats and requirements. Programmatic data migration may involve many phases but it minimally includes data extraction where data is read from the old system and data loading where data is written to the new system.

After loading into the new system, results are subjected to data verification to determine whether data was accurately translated, is complete, and supports processes in the new system. During verification, there may be a need for a parallel run of both systems to identify areas of disparity and forestall erroneous data loss.

Automated and manual data cleaning is commonly performed in migration to improve data quality, eliminate redundant or obsolete information, and match the requirements of the new system.

Data migration phases (design, extraction, cleansing, load, verification) for applications of moderate to high complexity are commonly repeated several times before the new system is deployed.

Migration as a form of Digital Preservation

Migration, which focuses on the digital object itself, is the act of transferring, or rewriting data from an out of date medium to a current medium and has for many years been considered the only viable approach to long-term preservation of digital objects ^[1]. Reproducing brittle newspapers onto microfilm is an example of such migration.

Disadvantages

• Migration addresses the possible obsolescence of the data carrier, but does not address the fact that certain technologies which run the data may be abandoned altogether, leaving migration useless.
• Time consuming - migration is a continual process, which must be repeated every time a media reaches obsolescence, for all data objects stored on a certain media.
• Costly - an institution must purchase additional data storage media at each a migration ^[2].

As a result of the disadvantages listed above, technology professionals have begun to develop alternatives to migration, such as emulation.

See also

• data conversion
• data transformation
• data mediation

References

1. ↑ van der Hoeven, Jeffery, Brian Lohman, and Remco Verdegem. "Emulation for Digital Preservation in Practice: The Results." The International Journal of Digital Curation 2.2 (2007): 123-132.
2. ↑ Muira, Gregory. "Pushing the Boundaries of Traditional Heritage Policy: maintaining long-term access to multimedia content." IFLA Journal 33 (2007): 323-326.

External links

Data migration tools

• Clover.ETL: open source data (LGPL) transformation/migration tool, engine based with pipeline-parallelism (also embeddable)
• Scriptella ETL: open source ETL and script execution tool used typically for database migration.
• ETL Integrator: JBI-enabled open source ETL tool for data migration in SOA environments.
• Data Migration Toolkit (DMT): freely available, GUI-based Java utility for migrating files and database data.
• Talend: open source code generation and script execution application for data transformation.
• CompareData: multi-threaded, cross-dbms ODBC data migration and synchronization.
• List of Data Migration Tools: Online searchable tool for identifying data migration vendor options.
• Independent Data Migration Community: Free online hub of resources for data migration professionals.

Other links

• Article on pitfalls of data migration planning and how to avoid them.

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