decodeDynamics

Data migration can be time-consuming, taking days or weeks depending on how much data you have. But there are strategies to make it faster. This blog explores these strategies to help you speed up your data migration.

• Limit the size of data: The very first thing would be to check the data which are really not required, highlight this to the key stakeholders if they really need this data and take data accordingly. An example to call out would be either de-activated records or closed cases/incidents long time ago.

• Data Cleanup: Planning your data cleanup strategy before the migration is crucial. It will save you a lot of time during the actual migration

• Staging Environments: Create a staging environment as a middle step between your data source and destination. Here, you can examine and make sure your data is in good shape before the final migration. It’s like a safety checkpoint for your data

• Master Data Lookups GUID: Establishing master data lookups using GUIDs in your staging server can optimize your data loading process. For instance, if you’re dealing with something like country codes as GUIDs and you need to associate them with Contact records, pre-set these GUIDs in your staging database. This preemptive step eliminates the need for additional server queries during the data load, making your process more efficient.

• Parallel Processing: To boost performance during migration, consider using the Migration utility on multiple servers for parallel processing or implement multi-threading.

• Data Transformation: Enhance migration speed by preparing and applying any necessary transformation logic on the staging server rather than the production environment. This approach minimizes the load on your production system and expedites the migration process.

• Upsert Method: There’s a performance penalty in using Upsert versus using Create. If you’re sure the record doesn’t exist, use Create

• GUID: Improve your data migration process by not allowing automatic GUID generation. Instead, generate GUIDs exclusively on the staging server.

• Option set/Drop Down Values: To enhance your data migration process, consider mapping option set values on the staging server in advance. This proactive step eliminates the need for database queries during the actual migration, resulting in improved efficiency and reduced data transfer times

• Custom Code: To improve the efficiency of your data migration, consider analyzing your custom code components. Identify essential tasks, like updating specific values, and see if they can be handled in the staging server instead of during create, update, or delete (CRUD) operations. This analysis can help streamline your migration process. Consider this example: when creating a “Contact” record, your custom code sets the contact’s country to “INDIA.” Instead of doing this during the actual record creation, consider handling such logic in the staging server. Review your code for similar opportunities to optimize your data migration.

The overall goal is to minimize the migration timeline, and you can achieve this by applying the practices and tips mentioned above. The key strategy is to minimize server queries during migration by conducting data transformations and mappings within the staging environment, effectively expediting the entire migration process.

This blog is a subset of Essential Design Considerations for Data Migration.