What is Data Migration/Conversion?
Data migration involves transferring data from a legacy system to a target system, ensuring data integrity, accuracy, and usability in the new environment. It often includes transforming data to match the structure and requirements of the target system.
What is Data Synchronization?
Data synchronization ensures that two systems (e.g., legacy and the target system) maintain consistent and up-to-date data during a phased migration. This is crucial when the new system goes live with a portion of the data, while the legacy system continues to operate for other functionalities. Synchronization enables both systems to “talk to each other” using mechanisms like APIs.
Phased Migration and Synchronization: A Real-World Scenario
Imagine this:
- Phase 1: A portion of data is migrated from the legacy system to the target system, and the target system begins to function for that subset of operations.
- However, the legacy system still requires the data in the new target system to function correctly for other processes.
The Solution: The target system sends the new data back to the legacy system using APIs. In some cases, the legacy system also updates the target system, or both systems exchange data bi-directionally.
Challenges in Migration and Synchronization
1. Mismatched Primary Keys
- If data migration and data synchronization do not use the same primary keys, chaos can ensue:
- Duplicates: Data might be entered as new records in one system because the existing record isn’t recognized.
- Data Loss or Confusion: Incorrect mappings can lead to missing relationships or misaligned updates.
2. Lack of Communication Between Teams
- Tight collaboration between the legacy and target system teams is essential:
- Clear documentation on data ownership, synchronization scope, and key structures.
- Shared understanding of how data flows between systems to avoid conflicting updates.
3. Insufficient Testing
- Without thorough testing, issues like duplicate records, misaligned updates, or system errors can occur. Rigorous testing is needed to:
- Validate data flows in both directions.
- Ensure business rules and logic are preserved.
- Confirm no critical data is lost in synchronization.
Types of Synchronization Scenarios
1. Data Sent from the Target System to the Legacy System (Majority Scope)
- Example: Migrated customer orders in the target system need to be synced back to the legacy system for financial processing.
- Key Need: Ensure that updates made in the target system are reliably reflected in the legacy system.
2. Data Sent from the Legacy System to the Target System (Limited Scope)
- Example: Certain financial metrics or historical data from the legacy system are pushed to the target system for reporting.
- Key Need: Avoid overwriting target system data by clearly defining what data the legacy system owns.
3. Bi-Directional Data Synchronization (Limited Scope)
- Example: Customer addresses are updated in either system and must reflect accurately in both.
- Key Need: Conflict resolution strategies to handle simultaneous updates in both systems.
Key Takeaways
- Plan for Primary Key Alignment: Ensure both systems recognize the same records by using shared keys or proper mapping.
- Communicate Clearly: Collaboration between teams is essential to prevent misunderstandings about data ownership and flow.
- Test Thoroughly: Simulate real-world scenarios during testing to uncover potential pitfalls before going live.
- Understand Synchronization Needs:
- Determine which system is the source of truth for specific data.
- Minimize bi-directional synchronization unless necessary to reduce complexity.
With a robust strategy for data migration and synchronization, phased transitions from legacy systems to a target system can be efficient and error-free. The key lies in meticulous planning, cross-team collaboration, and rigorous testing.
What has been your experience with phased migrations and synchronizing data between systems? Let’s discuss!