This book would be of interest to researchers and practitioners in the data analytics field. It examines the characteristics of big data; the uses of big data, including government, marketing, insurance, the Internet of Things, and healthcare; and different analytic approaches. The book is reasonably well organized and provides examples of the application of data analysis to various public and private sector organizations. Sufficient references are provided.

The field of big data analytics is still relatively new compared to other areas of computing and information systems. This book presents material that examines the current and future state of big data analytics. Given the level of mathematical notation within the book, it would generally be suitable for those researchers and practitioners with a first degree or higher in computer science, informatics, or mathematical sciences.

As well as presenting theoretical mathematical models of big data analysis and their applications in practice, the book also discusses the wider context of big data analytics, for example, the discrimination of speech and singing within big audio data, cloud-based scientific virtual laboratories, and unstructured data mining. There is a good balance between theory and the practical application of big data analytics. In terms of comparison with other books on big data, although it discusses the theory behind big data and provides practical applications, it perhaps lacks guidance on how a company or individual would typically approach the task of big data analysis (for example, how are suitable statistical methods and tools identified?).

This book’s main purpose would be as a reference work for practitioners and researchers in the big data analytics field who have at least a degree-level foundation in mathematics.