Data Modernization
Data Modernization Methods
There is no one-size-fits-all approach to data modernization. However, there are three general approaches enterprises take, depending on their business goals:
Data migration
- Involves moving data to a different vendor
- Source and target schemas remain the same
- Involves migrating code (procedures, etc.)
- Usually no major changes to the application
- Automation tools can be used to complete migration
- Example: Moving out of Oracle to save on licensing costs
Data conversion
- Source and target schemas are different
- Involves transformations during migration
- Typical during application re-engineering and legacy application modernization
- ETL tools are available, but process is manual
Database upgrade
- Involves upgrading to a newer version
- No transformation required
- Deprecated code is replaced
- Automation tools can be used to complete upgrade
- Example: Upgrading from SQL Server 2008 to SQL Server 2019
Our data modernization framework consists of three steps:
- Assessment – Stakeholders are consulted and a detailed data modernization strategy and methodology that aligns with the enterprise’s data modernization and business goals are defined
- Roadmap – A roadmap is determined for executing data modernization, beginning with the least risky data and moving towards more critical data
- Implementation – Multiple steps are taken to implement data modernization