Decision Support System for Government – BI Bridge
Led the design and development of an AI-driven Decision Support System (DSS) for a government client, enhancing decision-making with real-time data insights. Orchestrated a microservices architecture and agile workflows to deliver a scalable, dynamic data management platform. The system empowered stakeholders with predictive analytics and data visualization tools that reduced decision-making time by 20%. My work on the BI Bridge DSS reflects 2025's shift toward AI-enhanced, cloud-native decision support systems. Leveraging tools like .NET, Python, and Kubernetes, I built a platform akin to industry leaders like StrataJazz and Yonyx—delivering actionable insights with speed and scale. My focus on microservices and ML mirrors the modern DSS ethos: data-driven, agile, and impactful. The system ultimately streamlined government operations and provided a robust, data-driven toolset that transformed the client's decision-making processes.
Project Details
Key Features
- Built an AI-Powered DSS that integrated machine learning to cut decision-making time by 20%
- Empowered government stakeholders with predictive analytics and data visualization
- Designed a microservices architecture for scalability and performance
- Implemented a dynamic dashboard with real-time data insights similar to StrataJazz
- Developed decision-tree automation similar to Checkbox and Yonyx systems
- Created scenario-based strategic planning tools comparable to Parmenides Eidos
- Facilitated sprints, retrospectives, and planning as Scrum Master
Challenges
- Integrating multiple data sources in real-time for timely decision making
- Ensuring security and compliance for sensitive government data
- Scaling the system to handle increasing data volumes
- Balancing technical complexity with user-friendly interfaces
Solutions
- Implemented event-driven architecture for real-time data processing
- Developed strict access controls and encryption protocols
- Utilized Kubernetes for horizontal scaling and load balancing
- Created intuitive dashboards with React and Angular components
- Integrated JMP-like statistical analysis for "what-if" scenario modeling
- Established a Jenkins-based CI/CD pipeline that reduced deployment cycles by 25%
- Leveraged modern DSS design patterns for no-code accessibility and user-friendly interfaces
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