Keep it simple - Keep data in once place. No duplication. - Not everyone should have full-access to it. Give only required access. If someone should only consume the data, give read-only access. - Automate as much as possible - There should be someone and only one person accountable for the dataset. - Make sure you do regular audit & clean-up.

1. Standardize Data Policies Define clear rules for data ownership, access, and usage. Ensure alignment with industry regulations (e.g., GDPR, CCPA, HIPAA). 2. Implement a Centralized Data Platform Use data lakes or warehouses to consolidate data from different sources. Leverage ETL (Extract, Transform, Load) processes for consistency. 3. Ensure Data Quality & Security Apply data validation, cleansing, and deduplication techniques. Use role-based access controls (RBAC) and encryption for security. 4. Automate Compliance & Audits Utilize AI-powered tools for real-time monitoring and anomaly detection. Conduct periodic data governance audits. 5. Encourage Cross-Department Collaboration Assign data stewards to enforce

Managing data governance across various sources is indeed a complex task, but it’s essential for maintaining data integrity and compliance. I've seen firsthand how establishing clear protocols and fostering a culture of accountability can significantly streamline this process. It’s also crucial to leverage technology that integrates seamlessly with existing systems, ensuring that data remains accessible and reliable across platforms. This proactive approach not only mitigates risks but also empowers teams to make informed decisions based on accurate data.