A Medallion Architecture-Based Energy Consumption Monitoring Dashboard Using Databricks

Sarbeswar Mallick

Department of Master of Computer Applications

GIFT Autonomous, Bhubaneswar, Odisha, India, sarbeswarm2024@gift.edu.in

Smruti Ranjan Swain

Head of Department Master of Computer Applications

GIFT Autonomous, Bhubaneswar, Odisha, India, hodmca@gift.edu.in

Abstract—

Modern industries, smart buildings, and energy management systems generate a massive volume of energy consumption data every day through IoT sensors, smart meters, industrial equipment, and monitoring devices. Analyzing these large-scale datasets is essential for optimizing energy usage, improving operational efficiency, reducing energy costs, and supporting sustainable resource management.

This paper presents an Energy Consumption Monitoring Dashboard developed using the Databricks Lakehouse Platform and Medallion Architecture for scalable energy data processing and analytics. The proposed system processes energy datasets through Bronze, Silver, and Gold layers to improve data quality, perform transformations, and generate meaningful analytical insights.

Interactive dashboards are used to visualize energy consumption patterns, device-wise power usage, peak load analysis, energy trends, anomaly detection, and operational performance using various charts and analytical reports. The developed system helps energy managers, facility administrators, and organizations identify consumption patterns, monitor energy efficiency, and support data-driven decision-making for optimized energy utilization.

Furthermore, this work demonstrates how modern big data technologies and visualization tools can be effectively utilized in the energy sector for intelligent analytics, real-time monitoring, and sustainable energy management.

Keywords

Energy Consumption Analytics; Databricks; Medallion Architecture; Big Data Analytics; Energy Monitoring Dashboard; Data Visualization; Lakehouse Platform; IoT Analytics; Smart Energy Management; Real-Time Monitoring