Derive operational analytics from legacy data and explore inbound collaborative data integration options. The various use cases of Data migrations are policy data migration, claims and commissions data integration, new age legacy dw expansion, transactional data replication.
The approach of standardized data migration follows the 3-nuanced approach:
Object data migration model is extremely important in moving logical data. The following use cases are best fit for employing our object data migration model.
The business flow model along with analysis of interdepend ability, data consistency, object relation mapping, standard logical grouping will spur the first level of activities.
Further to this the foundation phase will be used to carve out a data use cases, and automation strategy including the high-level estimation and timeline for implementation.
The object data modelling involves creation of a logical MVP data module. This module should be the schema for the logical unit being extracted. The essential test attribute of a MVP would be to stand by itself as an enterprise component.
The other steps involved in creation of data model is to perform a data clean up and profiling. Once that is achieved the harmonization of data process is performed and proof of concept strategy along with implementation planning and dependencies diligence is done.
During the process, the mapped scripts to the object data model are leveraged to perform data extraction and migration of To Be state is done.
As the data is migrated and loaded into the target schemas, the data correctness check along with data completeness test along with straight processing for MVP use cases are performed to ascertain the validity of the data move.
Once the TO BE and As IS reconciliation report is analysed and consolidated, the object data model is further improvised and normalized considering the learnings and findings from the process. This is followed by release of control reports and sign off on the process