Analysis of Transformative Impact of Data Science on Energy

The energy business has experienced an exceptional increase in recent years due to the expanding significance of data science. Artificial intelligence, advanced analytics, and machine learning have allowed the energy sector to make enormous strides in predictive modeling, problem identification, and resource utilization management. Energy businesses may increase operational resilience, reduce risks, and make well-informed decisions using data-driven insights. Also, energy providers may better respond to the changing demands of their customers by customizing their offerings through big data analytics, which in turn creates a more flexible and approachable energy ecosystem. Data science is essential to grid management since it helps to optimize energy transmission and distribution. Real-time data analytics-enabled smart grids allow for effective fault detection, self-healing, and load balancing. The energy business is set to transform due to the integration of data science and technology, which will promote sustainability, resilience, and efficiency worldwide. This study reviews the applications of data science in the energy sector. Along with discussing these issues, the work also addresses the potential problems of new computing technology and completely connected devices.