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Applications of Big Data Analytics

Trends, Issues, and Challenges

  • Mohammed M. Alani
  • Hissam Tawfik
  • Mohammed Saeed
  • Obinna Anya

Table of contents

  1. Front Matter
    Pages i-xii
  2. Mohammed Dighriri, Gyu Myoung Lee, Thar Baker
    Pages 1-29
  3. Ahmed Afif Monrat, Raihan Ul Islam, Mohammad Shahadat Hossain, Karl Andersson
    Pages 31-42
  4. David Tian, Jiamei Deng, Gopika Vinod, T. V. Santhosh, Hissam Tawfik
    Pages 43-61
  5. D. G. Reina, T. Camp, A. Munjal, S. L. Toral, H. Tawfik
    Pages 63-95
  6. Mashail Alsalamah, Saad Amin, Vasile Palade
    Pages 97-120
  7. Ahmed J. Aljaaf, Conor Mallucci, Dhiya Al-Jumeily, Abir Hussain, Mohamed Alloghani, Jamila Mustafina
    Pages 121-134
  8. J. Artur Serrano, Hamzeh Awad, Ronny Broekx
    Pages 177-183
  9. Svitlana Yaremchuck, Vyacheslav Kharchenko, Anatoliy Gorbenko
    Pages 185-211
  10. Back Matter
    Pages 213-214

About this book

Introduction

This timely text/reference reviews the state of the art of big data analytics, with a particular focus on practical applications. An authoritative selection of leading international researchers present detailed analyses of existing trends for storing and analyzing big data, together with valuable insights into the challenges inherent in current approaches and systems. This is further supported by real-world examples drawn from a broad range of application areas, including healthcare, education, and disaster management. The text also covers, typically from an application-oriented perspective, advances in data science in such areas as big data collection, searching, analysis, and knowledge discovery.

Topics and features:

  • Discusses a model for data traffic aggregation in 5G cellular networks, and a novel scheme for resource allocation in 5G networks with network slicing
  • Explores methods that use big data in the assessment of flood risks, and apply neural networks techniques to monitor the safety of nuclear power plants
  • Describes a system which leverages big data analytics and the Internet of Things in the application of drones to aid victims in disaster scenarios
  • Proposes a novel deep learning-based health data analytics application for sleep apnea detection, and a novel pathway for diagnostic models of headache disorders
  • Reviews techniques for educational data mining and learning analytics, and introduces a scalable MapReduce graph partitioning approach for high degree vertices
  • Presents a multivariate and dynamic data representation model for the visualization of healthcare data, and big data analytics methods for software reliability assessment

This practically-focused volume is an invaluable resource for all researchers, academics, data scientists and business professionals involved in the planning, designing, and implementation of big data analytics projects.

Dr. Mohammed M. Alani is an Associate Professor in Computer Engineering and currently is the Provost at Al Khawarizmi International College, Abu Dhabi, UAE. Dr. Hissam Tawfik is a Professor of Computer Science in the School of Computing, Creative Technologies & Engineering at Leeds Beckett University, UK. Dr. Mohammed Saeed is a Professor in Computing and currently is the Vice President for Academic Affairs and Research at the University of Modern Sciences, Dubai, UAE. Dr. Obinna Anya is a Research Staff Member at IBM Research – Almaden, San Jose, CA, USA.

Keywords

Big Data Data Warehousing Search Algorithms Privacy Smart Cities

Editors and affiliations

  • Mohammed M. Alani
    • 1
  • Hissam Tawfik
    • 2
  • Mohammed Saeed
    • 3
  • Obinna Anya
    • 4
  1. 1.Al Khawarizmi International CollegeAbu DhabiUnited Arab Emirates
  2. 2.Leeds Beckett UniversityLeedsUnited Kingdom
  3. 3.University of Modern SciencesDubaiUnited Arab Emirates
  4. 4.IBM ResearchSan JoseUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-76472-6
  • Copyright Information Springer International Publishing AG, part of Springer Nature 2018
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science
  • Print ISBN 978-3-319-76471-9
  • Online ISBN 978-3-319-76472-6
  • Buy this book on publisher's site
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