Data Migration

Business Services

Data Migration

Migrating data is a challenging process with some significant risks attached. It is essential to plan, execute, and test as effectively as possible.


Data migration

Data migration is the process of selecting, preparing, extracting, and transforming data and permanently transferring it from one computer storage system to another.


Data migration is important because it is a necessary component to upgrading or consolidating server and storage hardware, or adding data-intensive applications like databases, data warehouses, and data lakes, and large-scale virtualization projects. Data migration may also occur within systems built on HDD or SDD, or between in-house systems and cloud storage.


Category of Data Migrations

The usual migration suspects include storage, database, application, cloud, and business process migration.


Migrating Storage

IT migrates data during a storage technology refresh. The goals of technology refreshes are faster performance and dynamic scaling along with improved data management features.


Migrating Databases

Migrating a database can mean moving between platforms, such as on-premise to the cloud, or migrating the data from one databases into a new one.


Migrating Applications

Application migration can mean moving data within an application, such as shifting from on-premises MS Office to Office 365 in the cloud. It can also mean replacing one application with a different one, such as moving from one accounting software to a new accounting platform from a different vendor.


Migrating to the Cloud

Cloud migration moves data from on-premises to a cloud, or from one cloud to another. This type of data movement is not the same as backing up to the cloud: data migration is a distinct project that moves data from the source environment to populate the new one.


Note that data migration is not the same thing as data conversion or data integration.


Data Migration

Moving data between storage devices, locations, or systems. Includes subsets like quality assurance, cleansing, validation, and profiling.


Data Conversion.

Transforms data from a legacy application to an updated or new application. The process is ETL: extract, transform, load.


Data Integration.

Combines stored data residing in different systems to create a unified view and global analytics.


While data migration at its simplest is the transfer of data, the full context of data migration includes several component processes.


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