Data migrations generally result from the introduction of a new system. This may involve an application migration or consolidation in which one or more legacy systems are replaced or the deployment of an additional system that will sit alongside the existing applications.
Steps To Design an Effective Data Conversion Process:
Below are the steps for effective data migration and conversion process for any implementations in ERP
. 1- Data Need for Conversion.
2- Data Mapping / Conversion Design
3- Finalization of Data for Migration
4- Loading of data for QA (Validation)
5- Data Migration /Data loading to Production.
6- Data Validations – Production
Data Need for Conversion:
The first point is to decide which data is required for conversion and requirement. It is normally depend on your implementations domain and modules. Which modules are implementing during the imp mentation and that basis it is decided what is the requirement of the data.
Data Mapping / Conversion Design
After identifying the data for migration the next stage is to make the conversion design and data mapping. Few are the important points for data conversion design.
- Extraction of data from Legacy System
- Templates for data loading
- Preparation of mapping sheet to map the legacy data to New system required data.
- Field to Field mapping of data legacy to required data.
- Legacy system data validation for mapping sheets.
- Data conversion if required during mapping and validation
Finalization of Data for Migration:
Once the Mapping is complete, the next step is to preparing and finalization of data for migration. This step is very crucial, because whatever data is finalized and migrated will be affected the performance of the ERP and it is saying garbage in and garbage out.
Each and every aspect of the data should be reviewed and analyzed that every piece of information that is required from the legacy data is available and converted into New system required form.
Data Migration Challenges
- Lack of Collaboration
- Lack of Standardization Poor System Design
- Inaccurate Information
- Poor interpretation of Business rules
Assumptions, Constraints and Risks
Assumption
- All severity 1 and 2 data exceptions originating from source data will be cleansed by the data cleanup team before the scheduled final data conversion execution.
- At the minimum, one key business subject matter expert per business domain will be available within 24 hours of the request.
- All environments (legacy, staging, and target) are fully documented (conceptual/logical data models, physical data model, business rules, and interfaces), available, and accessible by the data conversion team as scheduled.
- Only client records with “active” status as previously defined and agreed upon will be migrated over to new application system.
Constraints
- Data requirements and definitions may require clarification by Subject Matter Experts (SMEs).
- Expertise in legacy data may be limited or unavailable due to lack of documentation (e.g., data dictionary) or more pressing priorities such as production support.
Risks
- Migrating the entire data from legacy system to new system that could affect conversion feasibility , technical performance of the converted system, , the conversion schedule, costs, backup and recovery procedures.
- The data conversion plan may not be feasible to achieve the expected goals and objectives because data conversion scoping was based entirely on theory and previous experience.
- Data conversion effort may not be able to meet the planned schedule because the quality of source data is unknown.
