Applications Of Big Data Analytics

Download Applications Of Big Data Analytics PDF/ePub eBooks without registration on our website. Instant access to millions of titles from Our Library and it’s FREE to try! All books are in clear copy here, and all files are secure so don't worry about it.

If the content Applications Of Big Data Analytics not Found or Blank , you must refresh this page manually Or Can't wait? try our new eBooks Reader Platform

Applications Of Big Data Analytics


Applications Of Big Data Analytics pdf


File Size : 46,5 Mb
Total Download : 743

Author : Mohammed M. Alani
language : en
Publisher: Springer
Release Date : 2018-07-23



Download Applications Of Big Data Analytics written by Mohammed M. Alani and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-07-23 with Computers categories.


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.


Big Data Analytics


Big Data Analytics pdf


File Size : 53,6 Mb
Total Download : 704

Author : Saumyadipta Pyne
language : en
Publisher: Springer
Release Date : 2016-10-12



Download Big Data Analytics written by Saumyadipta Pyne and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-10-12 with Computers categories.


This book has a collection of articles written by Big Data experts to describe some of the cutting-edge methods and applications from their respective areas of interest, and provides the reader with a detailed overview of the field of Big Data Analytics as it is practiced today. The chapters cover technical aspects of key areas that generate and use Big Data such as management and finance; medicine and healthcare; genome, cytome and microbiome; graphs and networks; Internet of Things; Big Data standards; bench-marking of systems; and others. In addition to different applications, key algorithmic approaches such as graph partitioning, clustering and finite mixture modelling of high-dimensional data are also covered. The varied collection of themes in this volume introduces the reader to the richness of the emerging field of Big Data Analytics.


Data Intensive Computing Applications For Big Data


Data Intensive Computing Applications For Big Data pdf


File Size : 43,7 Mb
Total Download : 894

Author : M. Mittal
language : en
Publisher: IOS Press
Release Date : 2018-01-31



Download Data Intensive Computing Applications For Big Data written by M. Mittal and has been published by IOS Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-01-31 with Computers categories.


The book ‘Data Intensive Computing Applications for Big Data’ discusses the technical concepts of big data, data intensive computing through machine learning, soft computing and parallel computing paradigms. It brings together researchers to report their latest results or progress in the development of the above mentioned areas. Since there are few books on this specific subject, the editors aim to provide a common platform for researchers working in this area to exhibit their novel findings. The book is intended as a reference work for advanced undergraduates and graduate students, as well as multidisciplinary, interdisciplinary and transdisciplinary research workers and scientists on the subjects of big data and cloud/parallel and distributed computing, and explains didactically many of the core concepts of these approaches for practical applications. It is organized into 24 chapters providing a comprehensive overview of big data analysis using parallel computing and addresses the complete data science workflow in the cloud, as well as dealing with privacy issues and the challenges faced in a data-intensive cloud computing environment. The book explores both fundamental and high-level concepts, and will serve as a manual for those in the industry, while also helping beginners to understand the basic and advanced aspects of big data and cloud computing.


Big Data Analytics With Applications In Insider Threat Detection


Big Data Analytics With Applications In Insider Threat Detection pdf


File Size : 40,6 Mb
Total Download : 728

Author : Bhavani Thuraisingham
language : en
Publisher: CRC Press
Release Date : 2017-11-22



Download Big Data Analytics With Applications In Insider Threat Detection written by Bhavani Thuraisingham and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-11-22 with Computers categories.


Today's malware mutates randomly to avoid detection, but reactively adaptive malware is more intelligent, learning and adapting to new computer defenses on the fly. Using the same algorithms that antivirus software uses to detect viruses, reactively adaptive malware deploys those algorithms to outwit antivirus defenses and to go undetected. This book provides details of the tools, the types of malware the tools will detect, implementation of the tools in a cloud computing framework and the applications for insider threat detection.


Big Data Analytics Methods And Applications


Big Data Analytics Methods And Applications pdf


File Size : 48,7 Mb
Total Download : 871

Author : Jovan Pehcevski
language : en
Publisher: Arcler Press
Release Date : 2018-12



Download Big Data Analytics Methods And Applications written by Jovan Pehcevski and has been published by Arcler Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12 with Computers categories.


Big Data Analytics - Methods and Applications is a comprehensive book that examines various big data modelling and analytics approaches, infrastructure and security issues in analysis of big data, applications of big data in business, finance and management. Provides the readers with insights on methodology and applications of Big Data Analytics so as to understand the practical use of big data analytics along with the opportunities and challenges faced during the course.


Quantitative Analysis For System Applications


Quantitative Analysis For System Applications pdf


File Size : 46,8 Mb
Total Download : 203

Author : Daniel A. McGrath, Ph.D.
language : en
Publisher: Technics Publications
Release Date : 2018-09-05



Download Quantitative Analysis For System Applications written by Daniel A. McGrath, Ph.D. and has been published by Technics Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-05 with Computers categories.


As data holdings get bigger and questions get harder, data scientists and analysts must focus on the systems, the tools and techniques, and the disciplined process to get the correct answer, quickly! Whether you work within industry or government, this book will provide you with a foundation to successfully and confidently process large amounts of quantitative data. Here are just a dozen of the many questions answered within these pages: What does quantitative analysis of a system really mean? What is a system? What are big data and analytics? How do you know your numbers are good? What will the future data science environment look like? How do you determine data provenance? How do you gather and process information, and then organize, store, and synthesize it? How does an organization implement data analytics? Do you really need to think like a Chief Information Officer? What is the best way to protect data? What makes a good dashboard? What is the relationship between eating ice cream and getting attacked by a shark? The nine chapters in this book are arranged in three parts that address systems concepts in general, tools and techniques, and future trend topics. Systems concepts include contrasting open and closed systems, performing data mining and big data analysis, and gauging data quality. Tools and techniques include analyzing both continuous and discrete data, applying probability basics, and practicing quantitative analysis such as descriptive and inferential statistics. Future trends include leveraging the Internet of Everything, modeling Artificial Intelligence, and establishing a Data Analytics Support Office (DASO). Many examples are included that were generated using common software, such as Excel, Minitab, Tableau, SAS, and Crystal Ball. While words are good, examples can sometimes be a better teaching tool. For each example included, data files can be found on the companion website. Many of the data sets are tied to the global economy because they use data from shipping ports, air freight hubs, largest cities, and soccer teams. The appendices contain more detailed analysis including the 10 T’s for Data Mining, Million Row Data Audit (MRDA) Processes, Analysis of Rainfall, and Simulation Models for Evaluating Traffic Flow.


Handbook Of Big Data Analytics


Handbook Of Big Data Analytics pdf


File Size : 51,6 Mb
Total Download : 968

Author : Wolfgang Karl Härdle
language : en
Publisher: Springer
Release Date : 2018-07-20



Download Handbook Of Big Data Analytics written by Wolfgang Karl Härdle and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-07-20 with Computers categories.


Addressing a broad range of big data analytics in cross-disciplinary applications, this essential handbook focuses on the statistical prospects offered by recent developments in this field. To do so, it covers statistical methods for high-dimensional problems, algorithmic designs, computation tools, analysis flows and the software-hardware co-designs that are needed to support insightful discoveries from big data. The book is primarily intended for statisticians, computer experts, engineers and application developers interested in using big data analytics with statistics. Readers should have a solid background in statistics and computer science.