Ayavin Solutions
September 13, 2022

What is Data Migration?

  • Data migration is the process of moving data from one system to another. While this may appear to be a simple change, it implies a storage change as well as a database or application change.
  • Data is migrated by organizations for a variety of reasons. They might have to redesign an entire system, upgrade databases, build a new data warehouse, or merge new data from an acquisition. When deploying a new system along with existing applications, data migration is also required.

Why data migration is needed?

A thorough data migration strategy prevents an unsatisfactory experience that causes more problems. Incomplete plans can lead to migration projects failing, in addition to missing deadlines and exceeding budgets. 

Instead of subordinating migrations to another large-scale project, teams must give their full attention when planning and strategizing the work. Regardless of the specific reason for the data migration, the overall goal is to improve performance and industry growth. 

What is a data migration strategy?

  • Investigate and Assess the Source- 

Before you migrate data, you need to know and understand what you're migrating and how it fits into the target system. There may be data with many fields, some of which do not need to be mapped to the target system. 

There may also be missing data fields within a source that need to be retrieved from another location to fill in a gap. In that case Ask yourself what needs to be migrated, what can be left behind, and what might be missing. 

  • Plan the migration-

Organizations define the type of migration to undertake during the design phase. This includes sketching out the technical architecture of the solution and detailing the migration processes.

After considering the design, the data to be pulled over, and the target system, you can begin to define timelines and any project concerns. 

  • Construct the solution- 

A common strategy is to divide the data into subsets and build each category one at a time, followed by a test. If an organization is working on a particularly large migration, it may be advantageous to build and test concurrently.

The data migration is technically implemented. The data is extracted from the source systems, adapted to the quality requirements of the target system using different Transformation components, and finally uploaded to the target system.

  • Conduct a performance test- 

To ensure the accuracy of the implementation and the completeness of the application, it is essential to test the data migration design with real data.