Big data analytics presents a comprehensive treatment of the subject for undergraduate and postgraduate students of computer Science and engineering, information Technology, and other related disciplines. The book has been written to cover the basics of analytics before moving to big data and its analytics. It seeks to translate the theory behind big data into principles and practices for a data analyst. Key features br>Chapter outlines and learning outcomes listed at the start of each br>Chapter illustrative discussion on big data frameworks and infrastructure algorithms for data analytics on big data frameworks and tools solved numerical examples to supplement the text practice exercises and codes for various case studies on Hadoop, R, Spark, MongoDB, storm, and Neo4j interview questions highlighted as boxed items in each br>Chapter point-wise summary at the end of each br>Chapter to enable quick revision chapter-end exercises comprising objective-type questions with answers, critical thinking questions, descriptive type questions, and numerical exercises.

[Source: Oxford University Press]