An Overview of Data Migration Methodology for CSE Final Year Students

Introduction to An Overview of Data Migration Methodology:

Data migration generally refers to transferring of data between computer systems. Data migration is seen in most of the system implementations. There can be cases when data migration is to be done it can be with system redesign ,  and also  situations when existing systems upgrade to new systems or it can be a done as a process of data warehouse.

Everyone has view that two systems which maintain same sort of data might be doing similar things and can be mapped from one other easily. It is not the case. Legacy systems have proven historically at the atomic level of data with respect to integrity.

When dealing with hierarchical and relational systems, the two keystones of hierarchical systems includes de-normalization and redundant storage are two strategies are responsible for making relational cringe. To deal with all the above scenarios we need an approach by which organizations can handle migration projects.

The data migration project plan is divided into seven phases where the first phase is strategy, where strategy is easiest of all phases in planning where the focus of overall project is determined where all will be focusing on requirements of new system but not on data migration. Whereas the analysis phase includes identification of data sources which must be imported to the new system.

The next phase of Designing includes selection of each data element from list source data and then deciding to migrate or not. The build phase includes generation of new data structures and also creation of data structures within the data base. Whereas in testing and implementation phase’s errors are identified which can be either physical or logical and these errors can be rectified or cleaned in next phase of Revise. In the maintain phase all the mappings are validated and implemented successfully.

A decision has to be made regarding the data migration to be done manually or by a tool depends on the Organization.

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