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Book Big Data Analytics and Cloud Computing

Download or read book Big Data Analytics and Cloud Computing written by Marcello Trovati and published by Springer. This book was released on 2016-01-12 with total page 178 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book reviews the theoretical concepts, leading-edge techniques and practical tools involved in the latest multi-disciplinary approaches addressing the challenges of big data. Illuminating perspectives from both academia and industry are presented by an international selection of experts in big data science. Topics and features: describes the innovative advances in theoretical aspects of big data, predictive analytics and cloud-based architectures; examines the applications and implementations that utilize big data in cloud architectures; surveys the state of the art in architectural approaches to the provision of cloud-based big data analytics functions; identifies potential research directions and technologies to facilitate the realization of emerging business models through big data approaches; provides relevant theoretical frameworks, empirical research findings, and numerous case studies; discusses real-world applications of algorithms and techniques to address the challenges of big datasets.

Book Applications of Machine Learning in Big Data Analytics and Cloud Computing

Download or read book Applications of Machine Learning in Big Data Analytics and Cloud Computing written by Subhendu Kumar Pani and published by CRC Press. This book was released on 2022-09-01 with total page 346 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cloud Computing and Big Data technologies have become the new descriptors of the digital age. The global amount of digital data has increased more than nine times in volume in just five years and by 2030 its volume may reach a staggering 65 trillion gigabytes. This explosion of data has led to opportunities and transformation in various areas such as healthcare, enterprises, industrial manufacturing and transportation. New Cloud Computing and Big Data tools endow researchers and analysts with novel techniques and opportunities to collect, manage and analyze the vast quantities of data. In Cloud and Big Data Analytics, the two areas of Swarm Intelligence and Deep Learning are a developing type of Machine Learning techniques that show enormous potential for solving complex business problems. Deep Learning enables computers to analyze large quantities of unstructured and binary data and to deduce relationships without requiring specific models or programming instructions. This book introduces the state-of-the-art trends and advances in the use of Machine Learning in Cloud and Big Data Analytics. The book will serve as a reference for Data Scientists, systems architects, developers, new researchers and graduate level students in Computer and Data science. The book will describe the concepts necessary to understand current Machine Learning issues, challenges and possible solutions as well as upcoming trends in Big Data Analytics.

Book Big Data Analytics for Cloud  IoT and Cognitive Computing

Download or read book Big Data Analytics for Cloud IoT and Cognitive Computing written by Kai Hwang and published by John Wiley & Sons. This book was released on 2017-03-17 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt: The definitive guide to successfully integrating social, mobile, Big-Data analytics, cloud and IoT principles and technologies The main goal of this book is to spur the development of effective big-data computing operations on smart clouds that are fully supported by IoT sensing, machine learning and analytics systems. To that end, the authors draw upon their original research and proven track record in the field to describe a practical approach integrating big-data theories, cloud design principles, Internet of Things (IoT) sensing, machine learning, data analytics and Hadoop and Spark programming. Part 1 focuses on data science, the roles of clouds and IoT devices and frameworks for big-data computing. Big data analytics and cognitive machine learning, as well as cloud architecture, IoT and cognitive systems are explored, and mobile cloud-IoT-interaction frameworks are illustrated with concrete system design examples. Part 2 is devoted to the principles of and algorithms for machine learning, data analytics and deep learning in big data applications. Part 3 concentrates on cloud programming software libraries from MapReduce to Hadoop, Spark and TensorFlow and describes business, educational, healthcare and social media applications for those tools. The first book describing a practical approach to integrating social, mobile, analytics, cloud and IoT (SMACT) principles and technologies Covers theory and computing techniques and technologies, making it suitable for use in both computer science and electrical engineering programs Offers an extremely well-informed vision of future intelligent and cognitive computing environments integrating SMACT technologies Fully illustrated throughout with examples, figures and approximately 150 problems to support and reinforce learning Features a companion website with an instructor manual and PowerPoint slides www.wiley.com/go/hwangIOT Big-Data Analytics for Cloud, IoT and Cognitive Computing satisfies the demand among university faculty and students for cutting-edge information on emerging intelligent and cognitive computing systems and technologies. Professionals working in data science, cloud computing and IoT applications will also find this book to be an extremely useful working resource.

Book Cloud Computing for Geospatial Big Data Analytics

Download or read book Cloud Computing for Geospatial Big Data Analytics written by Himansu Das and published by Springer. This book was released on 2018-12-11 with total page 289 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces the latest research findings in cloud, edge, fog, and mist computing and their applications in various fields using geospatial data. It solves a number of problems of cloud computing and big data, such as scheduling, security issues using different techniques, which researchers from industry and academia have been attempting to solve in virtual environments. Some of these problems are of an intractable nature and so efficient technologies like fog, edge and mist computing play an important role in addressing these issues. By exploring emerging advances in cloud computing and big data analytics and their engineering applications, the book enables researchers to understand the mechanisms needed to implement cloud, edge, fog, and mist computing in their own endeavours, and motivates them to examine their own research findings and developments.

Book Challenges and Opportunities for the Convergence of IoT  Big Data  and Cloud Computing

Download or read book Challenges and Opportunities for the Convergence of IoT Big Data and Cloud Computing written by Velayutham, Sathiyamoorthi and published by IGI Global. This book was released on 2021-01-29 with total page 350 pages. Available in PDF, EPUB and Kindle. Book excerpt: In today’s market, emerging technologies are continually assisting in common workplace practices as companies and organizations search for innovative ways to solve modern issues that arise. Prevalent applications including internet of things, big data, and cloud computing all have noteworthy benefits, but issues remain when separately integrating them into the professional practices. Significant research is needed on converging these systems and leveraging each of their advantages in order to find solutions to real-time problems that still exist. Challenges and Opportunities for the Convergence of IoT, Big Data, and Cloud Computing is a pivotal reference source that provides vital research on the relation between these technologies and the impact they collectively have in solving real-world challenges. While highlighting topics such as cloud-based analytics, intelligent algorithms, and information security, this publication explores current issues that remain when attempting to implement these systems as well as the specific applications IoT, big data, and cloud computing have in various professional sectors. This book is ideally designed for academicians, researchers, developers, computer scientists, IT professionals, practitioners, scholars, students, and engineers seeking research on the integration of emerging technologies to solve modern societal issues.

Book Big Data Analytics and Cloud Computing

Download or read book Big Data Analytics and Cloud Computing written by Syed Thouheed Ahmed and published by MileStone Research Publications. This book was released on 2021-09-05 with total page 101 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big data analytics and cloud computing is the fastest growing technologies in current era. This text book serves as a purpose in providing an understanding of big data principles and framework at the beginner?s level. The text book covers various essential concepts of big-data analytics and processing tools such as HADOOP and YARN. The Textbook covers an analogical understanding on bridging cloud computing with big-data technologies with essential cloud infrastructure protocol and ecosystem concepts. PART I: Hadoop Distributed File System Basics, Running Example Programs and Benchmarks, Hadoop MapReduce Framework Essential Hadoop Tools, Hadoop YARN Applications, Managing Hadoop with Apache Ambari, Basic Hadoop Administration Procedures PART II: Introduction to Cloud Computing: Origins and Influences, Basic Concepts and Terminology, Goals and Benefits, Risks and Challenges. Fundamental Concepts and Models: Roles and Boundaries, Cloud Characteristics, Cloud Delivery Models, Cloud Deployment Models. Cloud Computing Technologies:Broadband networks and internet architecture, data center technology, virtualization technology, web technology, multi-tenant technology, service Technology Cloud Infrastructure Mechanisms:Logical Network Perimeter, Virtual Server, Cloud Storage Device, Cloud Usage Monitor, Resource Replication, Ready-made environment

Book Cloud Computing Enabled Big Data Analytics in Wireless Ad hoc Networks

Download or read book Cloud Computing Enabled Big Data Analytics in Wireless Ad hoc Networks written by Sanjoy Das and published by CRC Press. This book was released on 2022-03-21 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses intelligent computing through the Internet of Things (IoT) and Big-Data in vehicular environments in a single volume. It covers important topics, such as topology-based routing protocols, heterogeneous wireless networks, security risks, software-defined vehicular ad-hoc networks, vehicular delay tolerant networks, and energy harvesting for WSNs using rectenna. FEATURES Covers applications of IoT in Vehicular Ad-hoc Networks (VANETs) Discusses use of machine learning and other computing techniques for enhancing performance of networks Explains game theory-based vertical handoffs in heterogeneous wireless networks Examines monitoring and surveillance of vehicles through the vehicular sensor network Investigates theoretical approaches on software-defined VANET The book is aimed at graduate students and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer science, and engineering.

Book Handbook of Research on Cloud Infrastructures for Big Data Analytics

Download or read book Handbook of Research on Cloud Infrastructures for Big Data Analytics written by Raj, Pethuru and published by IGI Global. This book was released on 2014-03-31 with total page 592 pages. Available in PDF, EPUB and Kindle. Book excerpt: Clouds are being positioned as the next-generation consolidated, centralized, yet federated IT infrastructure for hosting all kinds of IT platforms and for deploying, maintaining, and managing a wider variety of personal, as well as professional applications and services. Handbook of Research on Cloud Infrastructures for Big Data Analytics focuses exclusively on the topic of cloud-sponsored big data analytics for creating flexible and futuristic organizations. This book helps researchers and practitioners, as well as business entrepreneurs, to make informed decisions and consider appropriate action to simplify and streamline the arduous journey towards smarter enterprises.

Book Big Data Analytics

    Book Details:
  • Author : V. B. Aggarwal
  • Publisher : Springer
  • Release : 2017-10-03
  • ISBN : 9811066205
  • Pages : 742 pages

Download or read book Big Data Analytics written by V. B. Aggarwal and published by Springer. This book was released on 2017-10-03 with total page 742 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume comprises the select proceedings of the annual convention of the Computer Society of India. Divided into 10 topical volumes, the proceedings present papers on state-of-the-art research, surveys, and succinct reviews. The volumes cover diverse topics ranging from communications networks to big data analytics, and from system architecture to cyber security. This volume focuses on Big Data Analytics. The contents of this book will be useful to researchers and students alike.

Book Big Data Analytics

    Book Details:
  • Author : Srinath Srinivasa
  • Publisher : Springer Science & Business Media
  • Release : 2012-12-15
  • ISBN : 3642355420
  • Pages : 192 pages

Download or read book Big Data Analytics written by Srinath Srinivasa and published by Springer Science & Business Media. This book was released on 2012-12-15 with total page 192 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the First International Conference on Big Data Analytics, BDA 2012, held in New Delhi, India, in December 2012. The 5 regular papers and 5 short papers presented were carefully reviewed and selected from 42 submissions. The volume also contains two tutorial papers in the section perspectives on big data analytics. The regular contributions are organized in topical sections on: data analytics applications; knowledge discovery through information extraction; and data models in analytics.

Book Applications of Big Data in Large  and Small Scale Systems

Download or read book Applications of Big Data in Large and Small Scale Systems written by Goundar, Sam and published by IGI Global. This book was released on 2021-01-15 with total page 377 pages. Available in PDF, EPUB and Kindle. Book excerpt: With new technologies, such as computer vision, internet of things, mobile computing, e-governance and e-commerce, and wide applications of social media, organizations generate a huge volume of data and at a much faster rate than several years ago. Big data in large-/small-scale systems, characterized by high volume, diversity, and velocity, increasingly drives decision making and is changing the landscape of business intelligence. From governments to private organizations, from communities to individuals, all areas are being affected by this shift. There is a high demand for big data analytics that offer insights for computing efficiency, knowledge discovery, problem solving, and event prediction. To handle this demand and this increase in big data, there needs to be research on innovative and optimized machine learning algorithms in both large- and small-scale systems. Applications of Big Data in Large- and Small-Scale Systems includes state-of-the-art research findings on the latest development, up-to-date issues, and challenges in the field of big data and presents the latest innovative and intelligent applications related to big data. This book encompasses big data in various multidisciplinary fields from the medical field to agriculture, business research, and smart cities. While highlighting topics including machine learning, cloud computing, data visualization, and more, this book is a valuable reference tool for computer scientists, data scientists and analysts, engineers, practitioners, stakeholders, researchers, academicians, and students interested in the versatile and innovative use of big data in both large-scale and small-scale systems.

Book High Performance Big Data Analytics

Download or read book High Performance Big Data Analytics written by Pethuru Raj and published by Springer. This book was released on 2015-10-16 with total page 443 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a detailed review of high-performance computing infrastructures for next-generation big data and fast data analytics. Features: includes case studies and learning activities throughout the book and self-study exercises in every chapter; presents detailed case studies on social media analytics for intelligent businesses and on big data analytics (BDA) in the healthcare sector; describes the network infrastructure requirements for effective transfer of big data, and the storage infrastructure requirements of applications which generate big data; examines real-time analytics solutions; introduces in-database processing and in-memory analytics techniques for data mining; discusses the use of mainframes for handling real-time big data and the latest types of data management systems for BDA; provides information on the use of cluster, grid and cloud computing systems for BDA; reviews the peer-to-peer techniques and tools and the common information visualization techniques, used in BDA.

Book Big Data

    Book Details:
  • Author : Rajkumar Buyya
  • Publisher : Morgan Kaufmann
  • Release : 2016-06-07
  • ISBN : 0128093463
  • Pages : 496 pages

Download or read book Big Data written by Rajkumar Buyya and published by Morgan Kaufmann. This book was released on 2016-06-07 with total page 496 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big Data: Principles and Paradigms captures the state-of-the-art research on the architectural aspects, technologies, and applications of Big Data. The book identifies potential future directions and technologies that facilitate insight into numerous scientific, business, and consumer applications. To help realize Big Data’s full potential, the book addresses numerous challenges, offering the conceptual and technological solutions for tackling them. These challenges include life-cycle data management, large-scale storage, flexible processing infrastructure, data modeling, scalable machine learning, data analysis algorithms, sampling techniques, and privacy and ethical issues. Covers computational platforms supporting Big Data applications Addresses key principles underlying Big Data computing Examines key developments supporting next generation Big Data platforms Explores the challenges in Big Data computing and ways to overcome them Contains expert contributors from both academia and industry

Book Research Anthology on Big Data Analytics  Architectures  and Applications

Download or read book Research Anthology on Big Data Analytics Architectures and Applications written by Information Resources Management Association and published by Engineering Science Reference. This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Society is now completely driven by data with many industries relying on data to conduct business or basic functions within the organization. With the efficiencies that big data bring to all institutions, data is continuously being collected and analyzed. However, data sets may be too complex for traditional data-processing, and therefore, different strategies must evolve to solve the issue. The field of big data works as a valuable tool for many different industries. The Research Anthology on Big Data Analytics, Architectures, and Applications is a complete reference source on big data analytics that offers the latest, innovative architectures and frameworks and explores a variety of applications within various industries. Offering an international perspective, the applications discussed within this anthology feature global representation. Covering topics such as advertising curricula, driven supply chain, and smart cities, this research anthology is ideal for data scientists, data analysts, computer engineers, software engineers, technologists, government officials, managers, CEOs, professors, graduate students, researchers, and academicians.

Book Big Data Analytics for Sustainable Computing

Download or read book Big Data Analytics for Sustainable Computing written by Haldorai, Anandakumar and published by IGI Global. This book was released on 2019-09-20 with total page 263 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big data consists of data sets that are too large and complex for traditional data processing and data management applications. Therefore, to obtain the valuable information within the data, one must use a variety of innovative analytical methods, such as web analytics, machine learning, and network analytics. As the study of big data becomes more popular, there is an urgent demand for studies on high-level computational intelligence and computing services for analyzing this significant area of information science. Big Data Analytics for Sustainable Computing is a collection of innovative research that focuses on new computing and system development issues in emerging sustainable applications. Featuring coverage on a wide range of topics such as data filtering, knowledge engineering, and cognitive analytics, this publication is ideally designed for data scientists, IT specialists, computer science practitioners, computer engineers, academicians, professionals, and students seeking current research on emerging analytical techniques and data processing software.

Book Cognitive Computing and Big Data Analytics

Download or read book Cognitive Computing and Big Data Analytics written by Judith S. Hurwitz and published by John Wiley & Sons. This book was released on 2015-04-08 with total page 291 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive guide to learning technologies that unlock the value in big data Cognitive Computing provides detailed guidance toward building a new class of systems that learn from experience and derive insights to unlock the value of big data. This book helps technologists understand cognitive computing's underlying technologies, from knowledge representation techniques and natural language processing algorithms to dynamic learning approaches based on accumulated evidence, rather than reprogramming. Detailed case examples from the financial, healthcare, and manufacturing walk readers step-by-step through the design and testing of cognitive systems, and expert perspectives from organizations such as Cleveland Clinic, Memorial Sloan-Kettering, as well as commercial vendors that are creating solutions. These organizations provide insight into the real-world implementation of cognitive computing systems. The IBM Watson cognitive computing platform is described in a detailed chapter because of its significance in helping to define this emerging market. In addition, the book includes implementations of emerging projects from Qualcomm, Hitachi, Google and Amazon. Today's cognitive computing solutions build on established concepts from artificial intelligence, natural language processing, ontologies, and leverage advances in big data management and analytics. They foreshadow an intelligent infrastructure that enables a new generation of customer and context-aware smart applications in all industries. Cognitive Computing is a comprehensive guide to the subject, providing both the theoretical and practical guidance technologists need. Discover how cognitive computing evolved from promise to reality Learn the elements that make up a cognitive computing system Understand the groundbreaking hardware and software technologies behind cognitive computing Learn to evaluate your own application portfolio to find the best candidates for pilot projects Leverage cognitive computing capabilities to transform the organization Cognitive systems are rightly being hailed as the new era of computing. Learn how these technologies enable emerging firms to compete with entrenched giants, and forward-thinking established firms to disrupt their industries. Professionals who currently work with big data and analytics will see how cognitive computing builds on their foundation, and creates new opportunities. Cognitive Computing provides complete guidance to this new level of human-machine interaction.

Book Emerging Trends in IoT and Integration with Data Science  Cloud Computing  and Big Data Analytics

Download or read book Emerging Trends in IoT and Integration with Data Science Cloud Computing and Big Data Analytics written by Taser, Pelin Yildirim and published by IGI Global. This book was released on 2021-11-05 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: The internet of things (IoT) has emerged to address the need for connectivity and seamless integration with other devices as well as big data platforms for analytics. However, there are challenges that IoT-based applications face including design and implementation issues; connectivity problems; data gathering, storing, and analyzing in cloud-based environments; and IoT security and privacy issues. Emerging Trends in IoT and Integration with Data Science, Cloud Computing, and Big Data Analytics is a critical reference source that provides theoretical frameworks and research findings on IoT and big data integration. Highlighting topics that include wearable sensors, machine learning, machine intelligence, and mobile computing, this book serves professionals who want to improve their understanding of the strategic role of trust at different levels of the information and knowledge society. It is therefore of most value to data scientists, computer scientists, data analysts, IT specialists, academicians, professionals, researchers, and students working in the field of information and knowledge management in various disciplines that include but are not limited to information and communication sciences, administrative sciences and management, education, sociology, computer science, etc. Moreover, the book provides insights and supports executives concerned with the management of expertise, knowledge, information, and organizational development in different types of work communities and environments.