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Data migration is the process of moving data from one location to another, one format to another, or one application to another. Generally, this is the result of introducing a new system or location for the data. The business driver is usually an application migration or consolidation in which legacy systems are replaced or augmented by new applications that will share the same dataset. These days, data migrations are often started as firms move from on-premises infrastructure and applications to cloud-based storage and applications to optimize or transform their company.
There are numerous business advantages to upgrading systems or extending a data center into the cloud. For many firms, this is a very natural evolution. Companies using cloud are hoping that they can focus their staff on business priorities, fuel top-line growth, increase agility, reduce capital expenses, and pay for only what they need on demand. However, the type of migration undertaken will determine how much IT staff time can be freed to work on other projects.
Storage migration: The process of moving data off existing arrays into more modern ones that enable other systems to access it. Offers significantly faster performance and more cost-effective scaling while enabling expected data management features such as cloning, snapshots, and backup and disaster recovery.
Cloud migration:The process of moving data, application, or other business elements from either an on-premises data center to a cloud or from one cloud to another. In many cases, it also entails a storage migration.
Application migration:The process of moving an application program from one environment to another. May include moving the entire application from an on-premises IT center to a cloud, moving between clouds, or simply moving the application’s underlying data to a new form of the application hosted by a software provider.
Moving important or sensitive data and decommissioning legacy systems can put stakeholders on edge. Having a solid plan is a must; however, you don’t have to reinvent the wheel. You can find numerous sample data migration plans and checklists on the web.
Premigration planning:Evaluate the data being moved for stability.
Project initiation:Identify and brief key stakeholders.
Landscape analysis:Establish a robust data quality rules management process and brief the business on the goals of the project, including shutting down legacy systems.
Solution design:Determine what data to move, and the quality of that data before and after the move.
Build & test:Code the migration logic and test the migration with a mirror of the production environment.
Execute & validate:Demonstrate that the migration has complied with requirements and that the data moved is viable for business use.
Decommission & monitor: Shut down and dispose of old systems.