<p>Modern energy systems are undergoing rapid transformations driven by carbon reduction policies, low-carbon technologies, and increasing digitalization, generating massive volumes of data. Leveraging big data and advanced data mining techniques enables the extraction of valuable insights that enhance the technical, operational, and economic performance of energy systems. In-depth analyses of energy systems using big data allow for the accumulation of vast amounts of information, which can then be transformed into meaningful knowledge with the help of data mining methods. This study presents a systematic survey of recent trends in big data and data mining applications in the energy domain, analyzing data types, processing methods, management challenges, and the limitations of both traditional and emerging technologies. This review seeks to highlight research areas that warrant greater focus in future studies. To support this analysis, we reviewed 56 articles published between 2020 and 2026 that investigate applications of big data and data mining in energy systems. This review examines key aspects of energy systems in cloud computing, including motivations, benefits, techniques, challenges, and applications, while highlighting algorithms and methods for efficient energy consumption management. The findings highlight that integrating big data analytics with data mining can make energy systems smarter, more flexible, and more responsive to operational changes, offering a clear perspective on the future of data-driven energy management.</p>