Implementing Data Governance in Power BI: Most organizations make informed decisions based on historical data trends and patterns. Every organization needs to maintain security and confidentiality. The IT/BI team is responsible for designing data collection, cleaning, and cataloging processes. They also develop rules for report creation and distribution within the organization. Every organization needs a robust and secure data governance system and framework. Data governance involves defining and enforcing policies, procedures, and standards for data management. 
Effective Power BI data governance ensures data integrity, security, and compliance, enabling data practitioners to utilize Power BI for analysis and reporting. Power BI provides tools to support this, ensuring data accuracy, reliability, and security. These include dataflows, datamarts, sensitivity labels, endorsement, discovery, and row-level security (RLS). Dataflows allow organizations to connect, clean, and transform data, while datamarts provide a centralized data repository. Sensitivity labels help to classify and protect sensitive data, while endorsement allows organizations to enforce data quality standards. Finally, Discovery helps organizations manage, monitor, and understand their data assets. Now we have Microsoft Fabric, which will be one source of truth for data in organizations implementing Microsoft Fabric.