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Data Science Consulting for Electric Energy Consumption Analysis and Forecasting

23 July 2025
Case Study
Publisher : ScienceSoft

15699

This case study describes how ScienceSoft implemented a data science solution for an energy provider to enhance energy consumption forecasting. By leveraging machine learning algorithms, the project enabled accurate load prediction, anomaly detection, and efficiency tracking across client sites. The developed solution included customised dashboards to visualise energy usage patterns, allowing for improved resource allocation and operational control. This intervention achieved a 30% boost in forecasting accuracy and reduced manual monitoring efforts significantly.

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ScienceSoft

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Key topics

Environmental Sustainability and Climate Action

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Technology for Social Change and Organisational Efficiency

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