Data migrations, often seen as daunting tasks, are crucial for modernizing data infrastructure, with the lift-and-shift approach being a popular strategy due to its simplicity and minimal changes to existing assets. This method involves transferring data from legacy systems to modern platforms like Snowflake or Databricks with minimal alterations, primarily focusing on ensuring business continuity and earning stakeholder trust. The lift-and-shift strategy is advantageous in terms of cost, time, and resource efficiency, as it allows companies to cease operations of outdated systems sooner, thereby reducing double maintenance expenses and enabling quicker access to new system benefits. Additionally, it mitigates risks associated with complex refactoring by maintaining structural similarities, which helps in building stakeholder confidence and ensuring a smoother transition. While alternative strategies like refactoring can optimize performance and resolve technical debt, they often introduce significant costs, extended timelines, and opportunity costs, diverting resources from other critical data initiatives.