Distributed Computing in Big Data Analytics : Concepts, Technologies and Applications

Description

Big data technologies are used to achieve any type of analytics in a fast and predictable way, thus enabling better human and machine level decision making. Principles of distributed computing are the keys to big data technologies and analytics. The mechanisms related to data storage, data access, data transfer, visualization and predictive modeling using distributed processing in multiple low cost machines are the key considerations that make big data analytics possible within stipulated cost and time practical for consumption by human and machines. However, the current literature available in big data analytics needs a holistic perspective to highlight the relation between big data analytics and distributed processing for ease of understanding and practitioner use. This book fills the literature gap by addressing key aspects of distributed processing in big data analytics. The chapters tackle the essential concepts and patterns of distributed computing widely used in big data analytics. This book discusses also covers the main technologies which support distributed processing. Finally, this book provides insight into applications of big data analytics, highlighting how principles of distributed computing are used in those situations. Practitioners and researchers alike will find this book a valuable tool for their work, helping them to select the appropriate technologies, while understanding the inherent strengths and drawbacks of those technologies. Read more... Abstract: Big data technologies are used to achieve any type of analytics in a fast and predictable way, thus enabling better human and machine level decision making. Principles of distributed computing are the keys to big data technologies and analytics. The mechanisms related to data storage, data access, data transfer, visualization and predictive modeling using distributed processing in multiple low cost machines are the key considerations that make big data analytics possible within stipulated cost and time practical for consumption by human and machines. However, the current literature available in big data analytics needs a holistic perspective to highlight the relation between big data analytics and distributed processing for ease of understanding and practitioner use. This book fills the literature gap by addressing key aspects of distributed processing in big data analytics. The chapters tackle the essential concepts and patterns of distributed computing widely used in big data analytics. This book discusses also covers the main technologies which support distributed processing. Finally, this book provides insight into applications of big data analytics, highlighting how principles of distributed computing are used in those situations. Practitioners and researchers alike will find this book a valuable tool for their work, helping them to select the appropriate technologies, while understanding the inherent strengths and drawbacks of those technologies Front Matter ....Pages i-ix On the Role of Distributed Computing in Big Data Analytics (Alba Amato)....Pages 1-10 Fundamental Concepts of Distributed Computing Used in Big Data Analytics (Qi Jun Wang)....Pages 11-34 Distributed Computing Patterns Useful in Big Data Analytics (Julio César Santos dos Anjos, Cláudio Fernando Resin Geyer, Jorge Luis Victória Barbosa)....Pages 35-55 Distributed Computing Technologies in Big Data Analytics (Kaushik Dutta)....Pages 57-82 Security Issues and Challenges in Big Data Analytics in Distributed Environment (Mayank Swarnkar, Robin Singh Bhadoria)....Pages 83-94 Scientific Computing and Big Data Analytics: Application in Climate Science (Subarna Bhattacharyya, Detelina Ivanova)....Pages 95-106 Distributed Computing in Cognitive Analytics (Vishwanath Kamat)....Pages 107-120 Distributed Computing in Social Media Analytics (Matthew Riemer)....Pages 121-135 Utilizing Big Data Analytics for Automatic Building of Language-agnostic Semantic Knowledge Bases (Khalifeh AlJadda, Mohammed Korayem, Trey Grainger)....Pages 137-160