"Big data" refers to large, diverse, complex, longitudinal, and/or distributed data sets generated from instruments, sensors, Internet transactions, email, video, click streams, and/or all other digital sources available today and in the future. Core techniques and technologies for advancing Big Data Science & Engineering aim to advance the core scientific and technological means of managing, analyzing, visualizing, and extracting useful information from large, diverse, distributed and heterogeneous data sets. "Big data" also implies that because of the vast amount of data a more structured engineering approach is necessary beyond more traditional data mining approaches to develop and implement data-driven engineering applications. Both in Europe and the US Big Data Analytics are being explored for applications in the sector of renewable energy. Big data analytics may offer a powerful analysis discipline, which is very appropriate in the area of more decentralized power generation, smart buildings and city quarters and transportation electrification. This presentation explains the origins and philosophy behind big data and addresses the state-of-the-art data science and engineering approaches and its potential impact on the way information can be extracted for advancing renewable energy applications.