Data migration is a critical step for companies aiming to modernize their analytics infrastructure, characterized by its high stakes, resource demands, and executive oversight. Successfully executing a migration not only builds trust but also positions a Systems Integrator (SI) to influence subsequent developments. Beyond transferring data, clients require new systems that are testable, scalable, and resilient, often without knowing how to achieve this independently. This presents an opportunity for SIs to implement foundational practices such as automated validation, continuous integration/continuous deployment (CI/CD) workflows, and embedded data testing. To ensure a successful migration and future collaboration, SIs can reduce risks and accelerate timelines by automating bottlenecks such as code translation and validation, proving success through data parity reports, and using the migration to establish improved defaults.