6 tips to prevent your data migration project from failing
Posted: Tue Jan 21, 2025 10:48 am
Having a project plan that includes enough time to analyze the risk of complexities is the best way to avoid data migration disasters.
The complexity of data migration projects can result in excessive costs and delays . Transferring data between systems is not a simple task and can lead to errors that can cause both a negative impact on the business, such as costly downtime, decreased user productivity, or the loss of important data.
Some of these issues can be avoided in a data migration project by doing some preparatory work beforehand and thinking through the process thoroughly. Here are some tips to help ensure that a database migration job goes off without a hitch .
Data migration, need and strategy
1. Clean the data
Initially everything is fine and the data is correct, but it is more than likely that over time and with use by multiple users, data inconsistencies and duplication have crept in. Therefore, it is important to clean up your data before starting your data migration project. Make sure to deduplicate the data and fix any integrity issues before these issues are replicated in the new system once the database migration is done.
2. Update business rules
Your company's business and validation rules may have linkedin database since the previous system was created. Now is the time to make sure that your company's rules are up to date and that any questions or process disputes about them are resolved. It's also a good idea to see if there are any data fields that need to be changed or added and that any necessary validations are included in the new database.
3. Check dependencies between objects
Often, dependencies between objects are not discovered until well into the data migration process. A complex project may have dozens of different data fields coming from different applications. Discovering new data sources or connectivity too late, well into the data migration process, can undermine the entire process . It is better to identify external data sources in advance and make sure you will have all the necessary connections in the new system.
4. Automate the data migration process whenever possible
Many projects run over budget due to human error and system outages. While traditional ETL tools may seem attractive to use from the start, they won’t allow you to maximize availability and keep business processes interconnected, such as automatically updating customer address data in your ERP based on changes recorded in your CRM. Instead, look for an integration platform that supports process-based integration . Additionally, an integration platform that has pre-built connectors for the systems you’re migrating can save a lot of time and help you avoid errors. It also allows you to keep both old and new systems up and running without the risk of downtime or lost transactions until you’re ready to make the full switch. Systems integration platforms can provide an effective solution that not only speeds up your data migration project but can be useful for other systems integration projects in the future, providing a high return on investment.
The complexity of data migration projects can result in excessive costs and delays . Transferring data between systems is not a simple task and can lead to errors that can cause both a negative impact on the business, such as costly downtime, decreased user productivity, or the loss of important data.
Some of these issues can be avoided in a data migration project by doing some preparatory work beforehand and thinking through the process thoroughly. Here are some tips to help ensure that a database migration job goes off without a hitch .
Data migration, need and strategy
1. Clean the data
Initially everything is fine and the data is correct, but it is more than likely that over time and with use by multiple users, data inconsistencies and duplication have crept in. Therefore, it is important to clean up your data before starting your data migration project. Make sure to deduplicate the data and fix any integrity issues before these issues are replicated in the new system once the database migration is done.
2. Update business rules
Your company's business and validation rules may have linkedin database since the previous system was created. Now is the time to make sure that your company's rules are up to date and that any questions or process disputes about them are resolved. It's also a good idea to see if there are any data fields that need to be changed or added and that any necessary validations are included in the new database.
3. Check dependencies between objects
Often, dependencies between objects are not discovered until well into the data migration process. A complex project may have dozens of different data fields coming from different applications. Discovering new data sources or connectivity too late, well into the data migration process, can undermine the entire process . It is better to identify external data sources in advance and make sure you will have all the necessary connections in the new system.
4. Automate the data migration process whenever possible
Many projects run over budget due to human error and system outages. While traditional ETL tools may seem attractive to use from the start, they won’t allow you to maximize availability and keep business processes interconnected, such as automatically updating customer address data in your ERP based on changes recorded in your CRM. Instead, look for an integration platform that supports process-based integration . Additionally, an integration platform that has pre-built connectors for the systems you’re migrating can save a lot of time and help you avoid errors. It also allows you to keep both old and new systems up and running without the risk of downtime or lost transactions until you’re ready to make the full switch. Systems integration platforms can provide an effective solution that not only speeds up your data migration project but can be useful for other systems integration projects in the future, providing a high return on investment.