Data migrations are frequently misunderstood, with many believing that the primary challenge lies in transferring data between platforms; however, the true difficulty often lies in migrating the accompanying code. While data can be moved swiftly and efficiently using open-source and SaaS tools like Airbyte and Fivetran, as well as native capabilities of data platforms, the process of migrating code is more complex and time-consuming. The challenge arises because code is tightly coupled with the specific engine it was created for, necessitating translation across different dialects and platforms, which complicates the task for data teams. This complexity is further exacerbated by the vast amount of code involved, which often includes a mix of languages, SQL scripts, and business logic embedded in outdated tools. As a result, even smaller-scale migrations can require several months to complete due to the need to translate and transfer thousands of models and transformations.