The Data Analytics Capability serves as a critical enabler for transforming governed and standardized data into actionable insights. It integrates tools and frameworks to support advanced data processing, analysis, and visualization across decentralized data assets. This capability facilitates descriptive and predictive analytics, statistical exploration, and the deployment of machine learning models for tasks such as categorization, clustering, and anomaly detection. The architecture emphasizes interoperability, ensuring seamless integration with diverse systems and scalability to handle growing data volumes and analytics workloads. Designed for secure and privacy-aware operations, the Data Analytics Capability incorporates role- and attribute based aaccess controls to safeguard insights. It supports real-time and batch data processing, producing consumable outputs via intuitive dashboards and reports. Leveraging modular design, it enables flexible analysis and decision-making while adhering to federated principles, allowing analytics to operate effectively across decentralized data ecosystems without compromising control or autonomy.