Data migration has been a core part of enterprise transformation for decades. Over that time, it has been learned that while the concept may seem straightforward, the execution is anything but. Data migration is a complex, iterative process that presents a range of challenges, especially when working with robust systems like IFS. In this article, we’ll explore three of the most common challenges and how we’ve developed solutions to overcome them.
1. Complex structures
IFS is a feature-rich platform with deep, interconnected datasets. This complexity means that nearly every data set we handle includes intricate parent/child relationships and dependencies. Ensuring that all data is migrated with the correct structure and relationships intact is one of the most difficult aspects of the process.
To address this, we’ve developed a suite of accelerators that simplify and streamline the migration of complex structures:
Solution-driven migration routines
These routines are tailored to IFS and help automate the creation of migration logic
Template documentation
Automatically generated templates break down complex structures into understandable formats
Table structure definitions
These include all fields, data types, List of Values (LOV) values, field lengths and DB values, providing clarity and reducing guesswork
