The big data tsunami changes the perspective of industrial and academic research in how they address both foundational questions and practical applications. This calls for a paradigm shift in algorithms and the underlying mathematical techniques. This book addresses algorithmic problems in the age of big data. 

Rapidly increasing volumes of diverse data from distributed sources create challenges for extracting valuable knowledge and commercial value from data. This motivates increased interest in the design and analysis of algorithms for rigorous analysis of such data. The book covers mathematically rigorous models, as well as some provable limitations of algorithms operating in those models. Most techniques discussed in the book come from research in the last decade. The algorithms discussed in the book have huge applications in web data compression, approximate query processing in databases, network measurement and signal processing.
This book is intended for both big data researchers, graduate students and advanced undergraduate students in computer and data science.