What is Efficient Data Migration & Integration
by Sarah Peter ContributorIn 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.
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Created on Sep 25th 2019 07:37. Viewed 497 times.