Industry

• Energy & Renewable Solutions

The Challenge

The client needed a centralized platform to efficiently create, manage, and monitor solar energy projects. Key requirements included:

• Project creation and management within a custom application.
• Detailed costing breakdown for each project segment.
• Dynamic project creation forms that adapt based on project type (e.g., Ground Mount, Rooftop, Canopy).
• Ability to assign projects to specific users depending on their roles.

The existing process lacked automation, dynamic data handling, and performance-optimized reporting, making it difficult to track progress, costs, and recovery rates effectively.

The Solution

The engagement involved architecting, designing, and implementing robust data aggregation and visualization capabilities, alongside predictive analytics. The key steps included:

1. Tableau Dashboard & Server Implementation
   • Designed and deployed interactive dashboards for project tracking, cost analysis, and recovery forecasting.
2. Predictive Recovery Model
   • Built a model to predict the probability of recovering claims, allowing classification into recovery probability buckets and enabling proactive decision-making.
3. Quality & Performance Optimization
   • Developed quality check reports to ensure accuracy of aggregated data.
   • Performance-tuned slow-running reports, improving data retrieval times significantly.
   • Recommended and implemented critical database design changes for efficiency.
4. Requirement Analysis & Iterative Enhancements
   • Collaborated with business stakeholders to capture evolving requirements.
   • Analysed, designed, and implemented feature enhancements based on operational needs.

Business Impact

• Enhanced Decision-Making : The predictive model provided actionable insights into claim recovery likelihood, helping prioritize recovery efforts and reduce losses.
• Operational Efficiency : Dynamic forms and role-based project assignment streamlined project creation and tracking, cutting down administrative time.
• Faster Reporting : Optimized dashboards and database design reduced report load times by over 50%, ensuring timely access to critical project data.
• Improved Data Accuracy : Quality-check mechanisms minimized reporting errors, boosting trust in analytics outputs.
• Scalability : The architecture allowed for easy integration of new project types and reporting requirements, future-proofing the system.

Technology Environment  

• BI & Visualization: Tableau Desktop, Tableau Server
• Database: SQL Server 2008