The two main data migration strategies are “big bang” and “trickle” migration. Big bang migration involves moving all your data in a single window. It leads to downtime for your new and old system, but once it’s done, it’s done.
Trickle migration has a “slow and steady wins the race” mentality. Systematically, your data will migrate from one system to the other over a period of weeks. Because this is less taxing on your systems, you can avoid downtime altogether and work while migrations are happening. Trickle migration also tends to have fewer problems along the way, provided you created a solid migration plan.
Validation and Testing
When you use trickle migration, it’s easier to perform data validation and testing as new data comes in. Validation can help you catch migration issues as soon as they arise, which is essential if you want to avoid them disappearing into your data lake. SAP data services can help you maintain data quality.
Predictive data quality is a great tool for automating work and granting you more control over your data. If you need a way to efficiently audit data with rules that adapt as you change practices, predictive data quality is your answer.
One of the best ways to ensure quality after the migration is with proper training. Whether you use trickle or big bang migration, your employees will need to understand a new system once the migration is complete. If you use trickle migration, that gives your employees time to learn the new system before all the data is transferred.
Now that you know these three tips for ensuring data quality in data migration, contact Chain-Sys Corporation for assistance with your next migration.