The energy and transport sectors are currently undergoing two main transformations: digitization and liberalization. Both transformations bring to the fore typical characteristics of big data scenarios: sensors, communication, computation, and control capabilities through increased digitization and automation of the infrastructure for operational efficiency leading to high-volume, high-velocity data. In liberalized markets, big data potential is realizable within consumerization scenarios and when the variety of data across organizational boundaries is utilized.In both sectors, there is a connotation that the term "big data" is not sufficient: the increasing computational resources embedded in the infrastructures can also be utilized to analyse data to deliver "smart data". The stakes are high, since the multimodal optimization opportunities are within critical infrastructures such as power systems and air travel, where human lives could be endangered, not just revenue streams.In order to identify the industrial needs and requirements for big data technologies, an analysis was performed of the available data sources in energy and transport as well as their use cases in the different categories for big data value: operational efficiency, customer experience, and new business models. The energy and transport sectors are quite similar when it comes to the prime characteristics regarding big data needs and requirements as well as future trends. A special area is
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