AGILE PLM | MIGRATION
Sustaining an efficient manufacturing business means that it will become necessary at some point to implement a new PLM solution. During this transition, all existing product data from the legacy platform will be migrated to the new solution at a point in the implementation phase.
The migration to Agile is a critical stage where a lot will go wrong if handled by the inexperienced.
Our Migration Process
Domain Systems’ Agile Consultants have the training, aptitude, and care necessary for completing a successful data transfer. The process of migrating your data to Agile can be broken down into a series of tasks, metrics, and procedures that reduce costs and time to completion.
The phases of the migration are:
- Data Extraction
- Data Mapping
- Data Transformation
- Data Import
- Database Test
- Repeat steps [as many times as needed]
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By signing up, one of our Agile Consultants will help you solidify your PLM strategy and answer any questions you may have about migrating to Agile PLM
Every data field that is going to be migrated from the source system to the target system must be defined and examined to ensure compliance with field lengths, data types, system rules, and other possible issues. It is critical to understand where information is going as well as if there are any known and avoidable obstacles in the way of a successful Agile PLM migration.
The data in a legacy system often contains problems or can be unknowingly incorrect due to any number of reasons. Any validation rule that can be utilized to locate and fix these problems is be performed on the first-pass data extract. Whereas the source system may ignore the discrepancies with items like duplicate reference designators on a Bill of Material, the target system typically will have tighter business rules.
Data is extracted from the source system and transformed—or translated—into a normalized format that the target system can import and understand. This transformation will not only perform the defined data mappings, but will also execute any underlying business logic functions that may be essential to populating more complex data structures.