Good morning, good afternoon, good evening, everyone. I'm k Sha a data management professional with over 15 years of experience in data governance, architecture, and business intelligence. Today, I'll walk you through how we implemented a scalable, secure, and compliance data governance framework for multi-tenant cloud environment. This isn't just about meeting regulatory requirement, but it's about building a system that evolves with your business. We face three core challenges, data isolation, ensuring each tenant data is segregated while enabling the cross cross system and while enabling the shared analytics. Regulatory complexity. Keeping up with the evolving laws like GDPR, hipaa CCPA across different regions and operational efficiencies. Maintaining strong controls without slowing down authorized access or performance. We needed a solution that made governance seamless and not bottleneck. These weren't theoretical problems. Our cloud infrastructure team in North America flagged only issue with data boundaries. The legal team in Europe surface compliance gaps and DevOps in Asia Pacific. Raised concern about security slowing down deployment. This global visibility helps shape a framework that is both comprehensive and flexible. We structured our governance framework around three pillars, tenant specific controls. So each organization defines its own security posture, secure data architecture, with role level security and tenant of encryptions reselling cloud infrastructure designed for redundancy and skill. This allowed us to embed governance directly into the system systems design, not vault in later data isolation strategies to isolate tenant data effectively. We use role level security in shared environment, ensuring that the data access is restricted by default. Each tenant sensitive information is encrypted. Using dedicated keys, ensuring data remains unreadable, even to privileged users. And we invented ownership metadata into every data element. Enforcing dynamic access policy, systemwide. This gave a strong separation without sacrificing performance and accessibility. Automated compliance engine, we built a compliance engine that works continuously and not just in the audit time. It monitors for discrepancy in real time, validate regulatory compliance, and alerts teams for potential. Violations. More importantly, it remediates automatically triggering corrective workflows and documenting the every action. This approach eliminates manual gaps and allows us to respond before issue escalates. Our security model is built in layers, starting with identity access management, using multifactor authentication and clear defined rules. Then data protection with masking and tokenization for sensitive fill and transport. Transport encryptions sec secures all data in motion while at raised encryption insurers long-term protection with distributed key management. This layer strategy ensures that even if one barrier fails, other stands ready. Operating globally means being flexible by design. We route data according to jurisdictional boundaries and apply region specific retention and data deletion policies. Our documentation system create audit ready reports that align with multiple standards simultaneously. This let us stay compliant without having to rebuild process. Every time a regulation changes, comprehensive audit capabilities, we make sure every user action and the data movement is fully traceable. Every access is logged, including who, what, when, and why. All contracts and data modifications are version control for accountability. Data exports are tracked and anomalies triggered alerts for investigation I this will trust both internally and with regulators. Let's look at what change after implementation. A 40% drop in compliance violation across several regions. 30% improvement in operational efficiency through automation. 65 reduction in the audit cycle time, freeing up both legal and IT teams, and 99.9% system up time proving that protection and performance can coexist. These gains were achieved through phase rollout and ongoing refinements. Here is how our implementation roadmap looked like. We started with the assessment where we map existing gaps and risk. Then we, the data governance architecture tailored to our business and regulatory profile. Build configured role-based access encryption layers and compliance automation and deploy. Rolled out gradually across functions and regions, constantly measuring and tuning along the way. This method ensured adoption, stability and continuous improvement. To close. Here are four co core takeaways. Complete tenant isolation achieved through layered controls and encryptions. Automated compliance achieved through by eliminating human error and delays and business agility with. Governance that doesn't slow teams down. Scalability allowing us to grow from thousand to tens of thousands of users with zero degradation and integrity. We built a governance foundation that is not just secure it, it's built to last. Thank you again for your time.