The process of transferring data from one data storage system to another and also between data formats and applications. It also involves data transfers between different data formats and applications.

Data Migration

Data migration is the process of transferring data from one storage system or computing environment to another. There are many reasons your enterprise might need to undertake a data migration project. For example, you might be replacing servers or storage devices or consolidating or decommissioning data center. Data migration is also an essential step in the overall process of migrating on-premises IT infrastructure to a cloud computing environment.

Whether you’re moving to a public cloud, private cloud, hybrid cloud, or multi-cloud environment, you’ll need to find a secure, cost-effective and efficient method of migrating your data to its new storage location.

Why A Data Migration Strategy Is Important?

Regardless of the exact purpose for a data migration, the goal is generally to enhance performance and competitiveness. Less successful migrations can result in inaccurate data that contains redundancies and unknowns. This can happen even when source data is fully usable and adequate. Further, any issues that did exist in the source data can be amplified when it’s brought into a new, more sophisticated system. A complete data migration strategy prevents a subpar experience that ends up creating more problems than it solves. Aside from missing deadlines and exceeding budgets, incomplete plans can cause migration projects to fail altogether. In planning and strategizing the work, teams need to give migrations their full attention, rather than making them subordinate to another project with a large scope.

     A strategic data migration plan should include consideration of these critical factors:

  • Knowing the data — Before migration, source data needs to undergo a complete audit. Unexpected issues can surface if this step is ignored.
  • Cleanup — Once you identify any issues with your source data, they must be resolved. This may require additional software tools and third-party resources because of the scale of the work.
  • Maintenance and protection — Data undergoes degradation after a period of time, making it unreliable. This means there must be controls in place to maintain data quality.
  • Governance — Tracking and reporting on data quality is important because it enables a better understanding of data integrity. The processes and tools used to produce this information should be highly usable and automate functions where possible.

In addition to a structured, step-by-step procedure, a data migration plan should include a process for bringing on the right software and tools for the project.