Enable the Intelligent Enterprise in Professional Services with Ayavin
Ayavin SolutionsSeptember 21, 2022
Types of data migration
There are numerous business advantages to upgrading systems or expanding a data center into the cloud. For many businesses, this is a natural progression. Companies that use the cloud hope to focus their employees on business priorities, fuel top-line growth, increase agility, cut capital expenses, and pay only for what they need on demand. However, the type of migration will determine how much time IT personnel can devote to other projects.
Let us first define the various types of migration:
- Relocation of storage-
Data migration from older arrays to newer ones that can be accessed by other systems. Provides significantly faster performance and more cost-effective scaling while supporting common data management features such as-
- An application migration -
The transfer of an application program from one environment to another. Cloud migration includes moving an entire application from an on-premises IT center to the cloud, moving between clouds, or simply moving the application's underlying data to a new form of application hosted by a software provider.
- The cloud migration-
Data, applications, or other business elements are moved from an on-premises data center to a cloud or from one cloud to another. Storage migration is frequently included.
How Data migration differs from data conversion and data integration.
Because the terms data migration and data conversion are sometimes used interchangeably on the internet, let us clarify that they are not synonymous. As previously stated, data migration is the process of moving data between locations, formats, or systems. Data migration includes data profiling, cleansing, and validation, as well as ongoing data quality assurance in the target system. In the majority of data migration scenarios, data conversion is only the first step in a lengthy process.
The process of converting data from one format to another is known as data conversion. When transferring data from a legacy application to an upgraded version of the same application or to a completely new application with a different structure, this is required. To be converted, data must be extracted from the source, altered, and loaded into the new target system based on a set of requirements.
Another term that is sometimes used interchangeably with data migration is data integration. The process of combining data from various sources to provide users with a unified view of all data is known as data integration. Data analytics necessitates the integration of data from various sources.