Data Migration: How to Avoid Mistakes

Data Migration

Data Migration refers to the process of importing and exporting huge data between different storage systems. This process may be accomplished manually by entering the data into the system, moving disk files from one folder (or computer) to another, and database insert queries. It can also be programmed digitally by developing custom software, or other methods. The specific method used for any particular system depends entirely on the systems involved and the nature and state of the data being migrated. Data migration becomes a crucial and often time-consuming factor when servers are replaced or upgraded.

Factors to Consider for Data Migration:

Data Volume: If the number of data being migrated does not have any negative impact on the new system or storage, data volume should not be an issue of concern. Moreover, if there is no barrier in bringing over a certain amount of data, migration in bulk can be done without any consequence. Again, before transferring huge data, the optimal performance of the new system has to be ensured.

Data Value: Filtering data before migration requires the users’ consent. It is best not to filter data at all while migrating. However, if there is a chance that older data may not work in the new system, with prior approval selected data can be omitted from migration.

Process of Data Migration:

Both the old and the new sources must be analyzed before performing data migration: how the systems work, who use the systems, and what are the systems used for. Reviewing the existing data in both the old and new systems will answer the three questions above. However, if the systems run any server processes related to the data, the data to be migrated must be analyzed and properly updated during the migration.

After analyzing the sources, required time for the migration has to be determined. If a seamless migration is not possible, the most appropriate time for the migration should be decided.

Technical compatibility issues often render the migrated data unusable due to data corruption. This is why post migration data verification is very important. Make sure the transferred data is compatible with the new platform and accessible with the installed apps.

Types of Data Migration:

Storage Migration: This is the moving of data from one type of disk to another. In this migration, the format and the content remain unchanged in the process.

Database Migration: Upgrading the database software and changing the database provider often requires data migration. Although updating database software may not require physical migration of data, changing service provider involves an unavoidable data migration.

Application Migration: This involves an obvious data migration as each application has its unique data model.

Business Process Migration: This is the combination of both storage and application based migration as a business involves data stored and used both by humans and applications.

Protecting Data During Migration:

Data corruption, loss, incompatibility, and other performance issues may arise during or after the migration process. This is why data integration is an inseparable part of data migration. The followings can be done to make sure that data migration is smooth and successful:

  • Monitor the entire data migration process meticulously
  • Have a clear idea of the data: it’s location, its format, the format it will take when migrated.
  • Extract, transform and deduplicate data before moving it.
  • Implement data migration policies so data is moved in an orderly manner.
  • Test and validate the migrated data to ensure it is accurate.
  • Audit and document the entire data migration process.


About the author


Business and technology have always been Sam's areas of interest, and he transformed that interest into a passion through his regular contributions on issues related to these. As an IT specialist Sam is well versed in the most up-to-date trends in the field of computer technology. He earned his Master's in Information Science from Penn State University. He writes on technology, science, business, nature, and contemporary issues.


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