Data Migration Process Defined
Data migration is a crucial operation within any enterprise and its failure can be catastrophic. So what are the stages of the successful data migration process? Here they are:
1. Source system exploration: Although source systems may contain thousands of fields, some might be not needed in the target system. During this stage, you have to identify, which data is required and where it is located. You also have to decide what data is redundant and not necessary for the migration.
2. Data assessment: Next, you have to assess the quality of the source data. If the new system fails due to data inconsistencies, incorrect or duplicate data, there is very limited value in migrating data to the target system. To assess the data, use the data profiling. Profiling identifies data defects at the table and column levels.
3. Data migration solution design: You have to define the technical architecture and design of the migration processes. In addition, you have to define the testing processes and determine whether there will be a one-way or bi-directional datamigration, whether you will purchase a data migration tool or build a customone.
4. Execution: In the majority of cases, the source systems are shut down during the data migration execution. In some cases, a zero-downtime migration approach may be needed. This requires data migration software to provide the initial load processes with additional data synchronization technology. It will allowcapturing changes and synchronizingthe source and target data after the initial load finishes.
5. Maintenance: There have to be ongoing data quality enhancements. You will need to manage data improvements and monitor the data quality of the new system.
Successful data migration is based on getting three things right: people, process and technology. Getting any one or more of these three wrong will damage the entire project.