A retail executive halted a $50 million expansion due to duplicate entries and outdated segments in quarterly data, highlighting the importance of data governance. Poor data governance can lead to missed opportunities, compliance risks, and costly errors, affecting 70% of organizations. A data governance maturity model offers a solution by assessing capabilities and mapping improvements, ensuring high data quality, effective policy implementation, and streamlined process optimization that aligns with business objectives. The model has five stages, each representing an increasing level of capability and integration, and selecting the right framework depends on factors such as current maturity level, industry regulations, company size, and long-term objectives. Organizations can assess their maturity by using stakeholder questionnaires, data audits, performance metrics, and other methods to identify gaps and track progress. To achieve data governance excellence, organizations must establish clear policies, prioritize data quality and security, promote cross-functional collaboration, leverage automation and AI, and operationalize governance with modern solutions like Acceldata. By doing so, they can unlock the full potential of their data and drive business performance.