This book covers the state-of-the-art analytics that encompass structured, semi-structured, and unstructured data for prediction, anomaly detection, pattern matching and data mining based on real-world scenarios. It presents background material in linear algebra, probability and statistics, and builds up the big data analytics algorithms from this base. It covers exploratory data analysis, supervised and unsupervised, text mining, and more, with an emphasis on practical applications through case studies. Some R and pseudocode will be included, and there are appendices giving further mathematical background. The book will be an ideal reference for anyone getting started in big data analytics.