Data transfer between different systems can lead to small errors creeping in. Even one part-per-million (PPM) level of error could be important, since there are hundreds of millions of records that are being transferred every day. These errors can harm your business if not proactively handled.
Data transfer is the transfer of data from an old system to a new one. This may happen due to several factors, like a change in business processes or technological advancements. In order to ensure data quality after the migration and minimal interruption of operations, a clear strategy for migration of system data is needed.
Data Migration Strategies
While the general attitude towards change can make data migration seem difficult to apply, it is definitely necessary. There are two main migration strategies that organizations planning a data migration can consider: a trickle migration or a big bang migration.
Big bang migrations include completing the whole migration in a defined, small processing window. This approach performs the migration in the shortest time, but it comes with several risks, such as an erosion of data quality due to a high pressure on migration teams to finish on schedule and avoid significant downtime of core systems.
Trickle migrations are an incremental approach to data migration. Instead of completing the whole event in a short time period, it involves running both old and new systems parallelly and transferring data in phases. This method actually causes minimal downtime to any applications and core systems that are constantly used by the business.
To choose the best methodology, the IT team needs to makes a decision after considering factors like:
- The time needed to complete migration activities
- Compatibility of systems and the underlying technologies
- Complexity and volume of data to be migrated
- Costs
A Standard Migration Process
- Project Scoping
You need to be clear about what is expected in terms of what the new systems can offer to your business. Realistic timelines have to be set in order to set these expectations.
- Migration Planning
During the preparation and planning phase, you need to ask fundamental questions like:
- What kind of data will be migrated, and what are its legal obligations?
- How will the data be migrated? Manually or by a specialist software?
Answering these questions will help you assess the effect of the migration on the project schedule and costs. You will also avoid compliance problems by ensuring that the migration is in line with regulatory obligations.
- Training
Training of end-users is a vital component of any data migration process. Trickle migrations usually tend to deliver the best results, as it will be easier to test what has been transferred. This reduces the effect on business due to system downtime or loss of data. Data also has to be incorporated to prevent the transfer of obsolete or invalid data types. However, no matter how successful a migration is, some clean-up is always necessary during the testing stage.
- Data Testing and Validation
A trickle migration helps to identify migration issues early on. The functional experts must make sure that the data has been correctly migrated.
- Post-Migration Support and Business Sign Off
It is important that there is an expert team available to identify and correct system issues that may come up post-migration. The project team must validate that data has been properly migrated, and all post-migration questions have been answered before the project sign off.
For any migration process to have the best chance of success, it has to be done in a way to maintain and improve the data quality. This is critical in increasing the value that businesses can derive from the information.