ABSTRACT
Data science is both a new concept and a recent field that has evolved with the concurrent growth of large-scale datasets and emerging technologies to handle a volume and variety of information from multiple sources and formats. The field draws heavily from several existing disciplines that we have discussed in this book: mathematics, statistics, computer science, geographic information systems (GIS), visualization, and more, including engineering, physics, psychology, cognitive science, operations research, business, and artificial intelligence. The primary aims entail the development and application of scientific approaches for the systematic exploitation, organization, management, analysis, and use of large amounts of data for decision making. Data science utilizes traditional or novel tools, methods, and strategies, which are tailored toward the discovery of complex patterns in highdimensional data through visualizations, simulations, and various types of model building (Kelling et al. 2009). It is being fueled by the critical need to design efficient, scalable, and reliable systems, tools, and programs that can easily handle “big data.”
