Change management is a critical component of effective data governance, ensuring that policies and procedures evolve in alignment with organizational growth. It involves a systematic approach to transitioning from current practices to improved ones by supporting and preparing stakeholders. Successful change management addresses potential pitfalls such as poor communication, lack of management buy-in, system integration issues, inadequate training, and unclear goals. Best practices for data change management include rolling out initiatives in phases, maintaining a single source of truth, clearly defining stakeholder roles, reviewing and approving dataset updates, keeping history logs, and conducting regular audits. These practices help ensure data accuracy, relevance, and consistency, ultimately facilitating smooth transitions and supporting organizational objectives.