What is Efficient Data Migration & Integration

by Sarah Peter Contributor

In simple words, data migration is the process of transferring data from a system (Source) to another system (target). It is perhaps the core task of any cog wheel offering migration and integration services like 4DS IT Limited. People seek such services when their company is merging with another, so it is necessary to create a bridge between the data centers of both companies for collaboration and coordination, that bridge is made possible through data migration & integration. Other than this, such services are also needed when a company is opening up a new branch or operations in a different place, that unit or branch is able to coordinate with the central data center of the company through efficient services of data migration.

An efficient data migration of reputable companies like 4DS IT Limited revolves around the following factors.

1)    Data Extraction, Transformation & Loading

This is the part of the process in which data is extracted from existing systems of the company, later on the same data is modified in accordance to the compatibility of new system where it is meant to be loaded, in technical terms this is called data transformation, as far as loading is concerned, it is just a name given to importing the extracted data into the destination database.

2)    Standardization

This is the part of data migration and integration process which standardizes or regulates specific terms or names across multiple data sources according to the business needs. For instance, an organization maybe entered into one system as “Chester Blogs” and entered into another system as “C.Blogs Ltd”. If the data is not optimized around standardized terms, it would result in duplicate entries which is a big problem as it would be impossible to link data from different sources, which means the users would be receiving inaccurate information (bad data). To avoid circumstances like these, reputable companies like 4DS IT Limited analyze data from every aspect before drafting a concrete migration strategy for their client.


3)    Data Cleansing

This process encapsulates everything that revolves around “correcting the data”. Following are 3 types of cleansing.

·         Structure cleansing

·         Critical data cleansing

·         Non-critical data cleansing

In structural cleansing, faults in the organization of individual data entries are corrected. The data is then split into critical and non-critical depending on whether the core business process can operate without it.

4)    Reconciliation

This is perhaps the final step of any efficient cog wheel of data migration & integration in which the migrated data is verified that it matches the database in the previous systems. The step is the final validation of the unified view presented in a data integration project.


About Sarah Peter Advanced   Contributor

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Joined APSense since, April 15th, 2017, From London, United Kingdom.

Created on Sep 25th 2019 08:37. Viewed 89 times.


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