Big data is a large and complex collection of data sets, which is difficult to process using on-hand database management tools and traditional data processing applications .Big Data Analytics is a rapidly evolving field that provides applications in many areas such as advertising, healthcare, medicine, marketing, and other Technology as well as welldefined in Computational view.

Big data are presented with the basic terms and concepts of Big Data computing.. Big Data topics are included in network and Computational activities:

This book provide well defined content on introduction part of Big Data and covers the subject in all basically defined aspects. It comprises of several aspects, sample codes, case studies and real-life analytics of datasets and classification. The book covers and serves the basic interests of undergraduate and post graduate students of computer science and engineering, information technology, and related disciplines. It will also to be useful to software developer’s inorder to highlight various basic needs of files system and arhitecrual view of that system.

Introduction to Big Data and Analytics book is good book for beginners and students. This book covers the following topics: introduction of big data its characteristics, hadoop, architecture of hadoop, hdfs , map reduce , with some practical knowledge. This book is designed to provide the students brief knowledge of big data concepts.

The coverage of piece of Big Data programming with open-source Big Data such as Map Reduce that follows a hierarchical Inclusion of latest topics of machine learning, predictive-analytics, similar and frequent item sets, clustering, classifiers and its recommended .This is predictive analysis and real-time streaming of data analytics.

The hierarchical and teach-by- example approach is solution for exercises and analysis are better topics for advanced learning for readers of the Book.