Data Migration Challenges
- The target system is usually under change during the project.
- Requirements cannot be known at start.
- Many requirement are discovered during the process.
- Many requirements change.
- All result in constant and expensive change control.
- Legacy systems contain a great deal of historical data which either has to be moved or dropped.
- This data either has to be moved completely or migrated into data warehouses and the target system.
- Older data requires more cleansing.
- All this has to be performed with full auditability and reconciled.
Data Migration Outcomes
- All data cleansed, reconfigured and moved in one operation.
- The migration is performed in a short controllable timeframe.
- The migration is fully audited and reconciled.
- Edge case data is dealt with, avoiding the need for exception reports.
- All historical data is present, avoiding the need run source systems past the end of the project.
- The source systems can be decommissioned immediately.
- Migration requirements are initially authored by the business team
- Initial implementation is developed (in a traditional language/tool) by technical/business team
- Complexity must be managed by hand in the implementation
- All errors, whether requirements or coding errors, must be discovered and put through change control.
- New requirements are discovered, target system changes, requirements change require costly change control
- Reruns are only possible after the change control process has occurred and the changes have been implemented – significantly limiting their frequency.
- Changes must be re-implemented and regression issues managed (are failures new requirements or regression issues)?
- As the project progresses exceptions become increasing difficult to manage and usually result in exception reporting – make reconciliation difficult.
- Final outcome is usual unsatisfactory.
acceler8’s Declarative Approach
- Business user develop requirements stand-alone (without having to understand the implementation.)
- Requirements are transformed automatically into the code that runs, avoid the traditional development step.
- This delivers significant error reduction.
- This also enables business users to easily change requirements and have the code change automatically.
- This reduces the costs of development and change control and greatly improves maintainability.
- Reruns can occur immediately the requirements have changed – which enables a significantly higher rerun frequency – potentially dozens a day.
- Requirements can be discovered late into the project to deal with exceptional cases without affecting the outcome.
- The requirements can be automatically compared to the known data models (source and target) for completeness checks and checked within themselves for consistency.
- Reconciliation checks and regression scripts can be automated from the same sources and run after each execution to aid analysis.
How do you know … ?
- It is important in any data migration project that you can be sure (even prove) the data was migrated correctly.
- You need to be able to answer any question starting with “How do you know ….?”
- The acceler8 data migration solution enables you to answer question like:
- How do you know the requirements are correct?
- How do you know all the data has been moved completely?
- How do you know the data is correct?
- How do you know the new system will operate correctly?