This book covers three major parts of Big Data: concepts theories and applications. Written by
world-renowned leaders in Big Data this book explores the problems possible solutions and
directions for Big Data in research and practice. It also focuses on high level concepts such
as definitions of Big Data from different angles surveys in research and applications and
existing tools mechanisms and systems in practice. Each chapter is independent from the other
chapters allowing users to read any chapter directly. After examining the practical side of
Big Data this book presents theoretical perspectives. The theoretical research ranges from Big
Data representation modeling and topology to distribution and dimension reducing. Chapters
also investigate the many disciplines that involve Big Data such as statistics data mining
machine learning networking algorithms security and differential geometry. The last section
of this book introduces Big Data applications from different communities such as business
engineering and science. Big Data Concepts Theories and Applications is designed as a
reference for researchers and advanced level students in computer science electrical
engineering and mathematics. Practitioners who focus on information systems big data data
mining business analysis and other related fields will also find this material valuable.
