Data Modernization

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

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