The maritime industry is transforming significantly to enhance energy efficiency and reduce environmental impacts, driven by global sustainability goals and stringent regulations. Advanced data analytics is pivotal in achieving these objectives by enabling data-driven decision-making and operational optimization. This study explores integrating advanced analytics techniques, including statistical methods, machine learning, and predictive modeling, to improve maritime energy efficiency. Key focus areas include fuel consumption optimization, emissions reduction, and route planning. By leveraging real-time data from ship sensors, weather forecasts, and operational records, advanced analytics provides actionable insights for stakeholders, leading to cost savings and enhanced compliance with environmental standards. The findings underscore the potential of data analytics to revolutionize maritime energy management, paving the way for a more sustainable and efficient future in the shipping industry.