This volume is aiming at a wide range of readers andresearchers in the area of Big Data by presenting the recent advances in the fieldsof Big Data Analysis, as well as the techniques and tools used to analyze it. The book includes 10 distinct chaptersproviding a concise introduction to Big Data Analysis and recent Techniques and Environments forBig Data Analysis. It gives insightinto how the expensive fitness evaluation of evolutionarylearning can play a vital role in big data analysis by adopting Parallel, Grid, and Cloud computing environments.

Introduction to Big Data Analysis.- Parallel Environments.- A Deep Dive into the Hadoop World to Explore its VariousPerformances.- Natural Language Processing and Machine Learning for Big Data.- Big Data and Cyber Foraging: Future Scope and Challenges.- Parallel GA in Big Data Analysis.- Evolutionary Algorithm Based Techniques to Handle Big Data.- Statistical and Evolutionary Feature Selection TechniquesParallelized using MapReduce Programming Model.- A Data Aware Scheme for Scheduling Big-Data Applications on SAVANNA Hadoop.- The Role of Grid Technologies: A Next Level Combat with Big Data.