Big data analysis techniques for intelligent systems

Recently, Internet of Things (IoT), Cloud, Big Data and AI gained a great attention as the most research topics. They cover not only information and communication technology, but also all kinds of intelligent systems in our society, including business, finance, industry, manufacture, management, and environment. As a result of the extensive use of these new technologies, a huge volume of data in different formats are generated much faster than before. Big data, characterized by high volume, variety and velocity, increasingly drives decision making and is changing the landscape of intelligent systems, from governments, organizations, communities to individual decision making. Cognitive big data analytics that discovers insights from pieces of evidence has a high demand for computing efficiency, knowledge discovery, problem-solving, and event prediction/prescription. It also poses great challenges in terms of data, process, analytical modelling and management for organizations to turn big data into big insight. Due to the increase in data size, complexity, and formats, it is no longer practical to anticipate and model all possible interactions and data processing in big data-based intelligent systems using the