ABSTRACT
INTRODUCTION Big Data is the buzzword everyone talks about since it concerns every human activity generating large quantities of digital data (e.g., science, government, economy). However, it is still dicult to characterize the Big Data phenomenon since dierent points of view
CONTENTS Introduction 43 e Big Data Vs 44
Variety 45 Volume 47 Velocity 47
Big Data-Processing Platforms 48 NoSQL Systems 48 Parallel Data Processing with MapReduce 49 Big Data Management Systems 50 Discussion 51
Big Data Life Cycle and Applications 51 Data Acquisition 51 Data Cleaning 52 Data Analysis and Mining 52 Big Data Aware Applications 52
Conclusions and Perspectives 53 References 54
and disciplines attempt to address it. It is true that everyone sees behind the term a data deluge for processing and managing big volumes of bytes (peta 1015, exa 1018, zetta 1021, yotta 1024, etc.). But beyond this supercial vision, there is a consensus about the three Vs [1] characterizing Big Data: volume, variety (dierent types of representations: structured, not-structured, graphs, etc.), and velocity (streams of data produced continuously).
