ABC aims to reduce operational costs and improve energy efficiency across its managed properties. The analysis seeks to identify key factors influencing energy consumption and provide actionable insights for optimization strategies. The dataset "Building_Energy_Consumption_Data" contains information on 100 buildings. Key variables include building type, floor area, energy consumption (kWh), occupancy rate, region, and energy score.

Industrial buildings in rural areas consume the most energy per square meter, while residential buildings have the lowest consumption across all regions. Urban areas generally use less energy for all building types. There’s a weak negative correlation between floor area and energy use, and a slight positive correlation with occupancy rate. Prioritize energy efficiency improvements in rural industrial buildings. Consider building type and usage patterns for optimization, as floor area and occupancy rate have weak correlations with energy use. Investigate operational efficiency, equipment upgrades, and energy management for effective energy-saving measures.

Performed exploratory data analysis (EDA) to understand the data. Calculated energy consumption per square meter. Investigated correlations between temperature, floor area, occupancy rates, and energy consumption. Created visualizations (heatmap, correlation plot, trend over time) to present insights.