Enerlytics is a web-based business intelligence dashboard project that analyzes global energy and environmental insights across sectors, regions, and risk dimensions.
The project transforms structured insight data into an interactive, executive-friendly dashboard to support strategic decision-making, built using React.js for frontend and Node.js + Express for backend APIs.
This project focuses on:
- Energy and environmental trends
- Sector-wise and geographic intelligence
- Risk assessment using intensity and likelihood metrics
- PESTLE-based contextual analysis
The dashboard is designed as a single-page BI view with logical sections for fast insight consumption.
- Frontend: React.js
- Backend: Node.js, Express.js (RESTful APIs)
- Database / Data Source: MongoDB
- Charts & Visualizations: Recharts
- Version Control & Documentation: GitHub
- Total Insights
- Total Sectors Covered
- Total Countries Covered
- Average Intensity
- Average Likelihood
- High Impact Insights
- Insights by Sector
- Top Discussed Topics (Oil, Gas, Consumption, etc.)
- Sector vs Topic distribution
- Country-level insight distribution
- Region vs Sector comparison
- Risk Matrix (Likelihood vs Intensity)
- Intensity distribution across insights
- Identification of high-impact, medium-likelihood issues
- PESTLE category distribution
- Time-based trends using published dates
- Detailed drill-down table
- Interactive filtering across all dimensions
Enerlytics supports:
- Business Intelligence & Reporting
- Strategic Planning
- Market & Sustainability Monitoring
- Executive Decision Support
The dashboard helps stakeholders quickly understand what is happening, where, and how impactful it is.
Each record in the dataset represents a curated insight with attributes such as:
- Sector
- Topic
- Country & Region
- Intensity, Likelihood, Relevance
- PESTLE Category
- Source & Publication Date
- Energy sector dominates global insights
- Oil and gas remain primary focus topics
- Northern America is the most represented region
- Most insights fall into medium-likelihood, high-impact category
- Environmental risks are region-specific and supply-chain driven