Data Science And Big Data Computing

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Data Science and Big Data Computing

Zaigham Mahmood
Data Science and Big Data Computing Book PDF

Author : Zaigham Mahmood
Publisher : Springer
Page : 319 pages
File Size : 53,9 Mb
Release : 2016-07-05
Category : Business & Economics
ISBN : 9783319318615

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Data Science and Big Data Computing by Zaigham Mahmood Pdf

This illuminating text/reference surveys the state of the art in data science, and provides practical guidance on big data analytics. Expert perspectives are provided by authoritative researchers and practitioners from around the world, discussing research developments and emerging trends, presenting case studies on helpful frameworks and innovative methodologies, and suggesting best practices for efficient and effective data analytics. Features: reviews a framework for fast data applications, a technique for complex event processing, and agglomerative approaches for the partitioning of networks; introduces a unified approach to data modeling and management, and a distributed computing perspective on interfacing physical and cyber worlds; presents techniques for machine learning for big data, and identifying duplicate records in data repositories; examines enabling technologies and tools for data mining; proposes frameworks for data extraction, and adaptive decision making and social media analysis.

High-Performance Big Data Computing

Dhabaleswar K. Panda,Xiaoyi Lu,Dipti Shankar
High Performance Big Data Computing Book PDF

Author : Dhabaleswar K. Panda,Xiaoyi Lu,Dipti Shankar
Publisher : MIT Press
Page : 275 pages
File Size : 54,9 Mb
Release : 2022-08-02
Category : Computers
ISBN : 9780262369428

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High-Performance Big Data Computing by Dhabaleswar K. Panda,Xiaoyi Lu,Dipti Shankar Pdf

An in-depth overview of an emerging field that brings together high-performance computing, big data processing, and deep lLearning. Over the last decade, the exponential explosion of data known as big data has changed the way we understand and harness the power of data. The emerging field of high-performance big data computing, which brings together high-performance computing (HPC), big data processing, and deep learning, aims to meet the challenges posed by large-scale data processing. This book offers an in-depth overview of high-performance big data computing and the associated technical issues, approaches, and solutions. The book covers basic concepts and necessary background knowledge, including data processing frameworks, storage systems, and hardware capabilities; offers a detailed discussion of technical issues in accelerating big data computing in terms of computation, communication, memory and storage, codesign, workload characterization and benchmarking, and system deployment and management; and surveys benchmarks and workloads for evaluating big data middleware systems. It presents a detailed discussion of big data computing systems and applications with high-performance networking, computing, and storage technologies, including state-of-the-art designs for data processing and storage systems. Finally, the book considers some advanced research topics in high-performance big data computing, including designing high-performance deep learning over big data (DLoBD) stacks and HPC cloud technologies.

Big Data, Cloud Computing, Data Science & Engineering

Roger Lee
Big Data Cloud Computing Data Science Engineering Book PDF

Author : Roger Lee
Publisher : Springer
Page : 189 pages
File Size : 42,8 Mb
Release : 2018-08-13
Category : Technology & Engineering
ISBN : 9783319968032

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Big Data, Cloud Computing, Data Science & Engineering by Roger Lee Pdf

This book presents the outcomes of the 3rd IEEE/ACIS International Conference on Big Data, Cloud Computing, Data Science & Engineering (BCD 2018), which was held on July 10–12, 2018 in Kanazawa. The aim of the conference was to bring together researchers and scientists, businesspeople and entrepreneurs, teachers, engineers, computer users, and students to discuss the various fields of computer science, to share their experiences, and to exchange new ideas and information in a meaningful way. All aspects (theory, applications and tools) of computer and information science, the practical challenges encountered along the way, and the solutions adopted to solve them are all explored here. The conference organizers selected the best papers from among those accepted for presentation. The papers were chosen on the basis of review scores submitted by members of the program committee and subsequently underwent further rigorous review. Following this second round of review, 13 of the conference’s most promising papers were selected for this Springer (SCI) book. We eagerly await the important contributions that we know these authors will make to the field of computer and information science.

Data Science and Big Data Analytics in Smart Environments

Marta Chinnici,Florin Pop,Catalin Negru
Data Science and Big Data Analytics in Smart Environments Book PDF

Author : Marta Chinnici,Florin Pop,Catalin Negru
Publisher : CRC Press
Page : 305 pages
File Size : 47,8 Mb
Release : 2021-07-28
Category : Computers
ISBN : 9781000386011

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Data Science and Big Data Analytics in Smart Environments by Marta Chinnici,Florin Pop,Catalin Negru Pdf

Most applications generate large datasets, like social networking and social influence programs, smart cities applications, smart house environments, Cloud applications, public web sites, scientific experiments and simulations, data warehouse, monitoring platforms, and e-government services. Data grows rapidly, since applications produce continuously increasing volumes of both unstructured and structured data. Large-scale interconnected systems aim to aggregate and efficiently exploit the power of widely distributed resources. In this context, major solutions for scalability, mobility, reliability, fault tolerance and security are required to achieve high performance and to create a smart environment. The impact on data processing, transfer and storage is the need to re-evaluate the approaches and solutions to better answer the user needs. A variety of solutions for specific applications and platforms exist so a thorough and systematic analysis of existing solutions for data science, data analytics, methods and algorithms used in Big Data processing and storage environments is significant in designing and implementing a smart environment. Fundamental issues pertaining to smart environments (smart cities, ambient assisted leaving, smart houses, green houses, cyber physical systems, etc.) are reviewed. Most of the current efforts still do not adequately address the heterogeneity of different distributed systems, the interoperability between them, and the systems resilience. This book will primarily encompass practical approaches that promote research in all aspects of data processing, data analytics, data processing in different type of systems: Cluster Computing, Grid Computing, Peer-to-Peer, Cloud/Edge/Fog Computing, all involving elements of heterogeneity, having a large variety of tools and software to manage them. The main role of resource management techniques in this domain is to create the suitable frameworks for development of applications and deployment in smart environments, with respect to high performance. The book focuses on topics covering algorithms, architectures, management models, high performance computing techniques and large-scale distributed systems.

Big Data Computing

Rajendra Akerkar
Big Data Computing Book PDF

Author : Rajendra Akerkar
Publisher : CRC Press
Page : 566 pages
File Size : 44,9 Mb
Release : 2013-12-05
Category : Business & Economics
ISBN : 9781466578371

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Big Data Computing by Rajendra Akerkar Pdf

Due to market forces and technological evolution, Big Data computing is developing at an increasing rate. A wide variety of novel approaches and tools have emerged to tackle the challenges of Big Data, creating both more opportunities and more challenges for students and professionals in the field of data computation and analysis. Presenting a mix of industry cases and theory, Big Data Computing discusses the technical and practical issues related to Big Data in intelligent information management. Emphasizing the adoption and diffusion of Big Data tools and technologies in industry, the book introduces a broad range of Big Data concepts, tools, and techniques. It covers a wide range of research, and provides comparisons between state-of-the-art approaches. Comprised of five sections, the book focuses on: What Big Data is and why it is important Semantic technologies Tools and methods Business and economic perspectives Big Data applications across industries

Data Science and Big Data Analytics

EMC Education Services
Data Science and Big Data Analytics Book PDF

Author : EMC Education Services
Publisher : John Wiley & Sons
Page : 432 pages
File Size : 41,5 Mb
Release : 2015-01-05
Category : Computers
ISBN : 9781118876053

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Data Science and Big Data Analytics by EMC Education Services Pdf

Data Science and Big Data Analytics is about harnessing the power of data for new insights. The book covers the breadth of activities and methods and tools that Data Scientists use. The content focuses on concepts, principles and practical applications that are applicable to any industry and technology environment, and the learning is supported and explained with examples that you can replicate using open-source software. This book will help you: Become a contributor on a data science team Deploy a structured lifecycle approach to data analytics problems Apply appropriate analytic techniques and tools to analyzing big data Learn how to tell a compelling story with data to drive business action Prepare for EMC Proven Professional Data Science Certification Get started discovering, analyzing, visualizing, and presenting data in a meaningful way today!

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

Subhendu Kumar Pani,Somanath Tripathy,George Jandieri,Sumit Kundu,Talal Ashraf Butt
Applications of Machine Learning in Big Data Analytics and Cloud Computing Book PDF

Author : Subhendu Kumar Pani,Somanath Tripathy,George Jandieri,Sumit Kundu,Talal Ashraf Butt
Publisher : CRC Press
Page : 346 pages
File Size : 51,5 Mb
Release : 2022-09-01
Category : Technology & Engineering
ISBN : 9781000793550

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Applications of Machine Learning in Big-Data Analytics and Cloud Computing by Subhendu Kumar Pani,Somanath Tripathy,George Jandieri,Sumit Kundu,Talal Ashraf Butt Pdf

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.

Big-Data Analytics for Cloud, IoT and Cognitive Computing

Kai Hwang,Min Chen
Big Data Analytics for Cloud IoT and Cognitive Computing Book PDF

Author : Kai Hwang,Min Chen
Publisher : John Wiley & Sons
Page : 432 pages
File Size : 50,8 Mb
Release : 2017-03-17
Category : Computers
ISBN : 9781119247296

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Big-Data Analytics for Cloud, IoT and Cognitive Computing by Kai Hwang,Min Chen Pdf

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.

Distributed Computing in Big Data Analytics

Sourav Mazumder,Robin Singh Bhadoria,Ganesh Chandra Deka
Distributed Computing in Big Data Analytics Book PDF

Author : Sourav Mazumder,Robin Singh Bhadoria,Ganesh Chandra Deka
Publisher : Springer
Page : 162 pages
File Size : 52,5 Mb
Release : 2017-08-29
Category : Computers
ISBN : 9783319598345

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Distributed Computing in Big Data Analytics by Sourav Mazumder,Robin Singh Bhadoria,Ganesh Chandra Deka Pdf

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.

Big-Data Analytics and Cloud Computing

Marcello Trovati,Richard Hill,Ashiq Anjum,Shao Ying Zhu,Lu Liu
Big Data Analytics and Cloud Computing Book PDF

Author : Marcello Trovati,Richard Hill,Ashiq Anjum,Shao Ying Zhu,Lu Liu
Publisher : Springer
Page : 169 pages
File Size : 55,6 Mb
Release : 2016-01-12
Category : Computers
ISBN : 9783319253138

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Big-Data Analytics and Cloud Computing by Marcello Trovati,Richard Hill,Ashiq Anjum,Shao Ying Zhu,Lu Liu Pdf

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.

Big Data Analytics for Sustainable Computing

Haldorai, Anandakumar,Ramu, Arulmurugan
Big Data Analytics for Sustainable Computing Book PDF

Author : Haldorai, Anandakumar,Ramu, Arulmurugan
Publisher : IGI Global
Page : 263 pages
File Size : 53,9 Mb
Release : 2019-09-20
Category : Computers
ISBN : 9781522597520

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Big Data Analytics for Sustainable Computing by Haldorai, Anandakumar,Ramu, Arulmurugan Pdf

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.

Big Data Science and Analytics for Smart Sustainable Urbanism

Simon Elias Bibri
Big Data Science and Analytics for Smart Sustainable Urbanism Book PDF

Author : Simon Elias Bibri
Publisher : Springer
Page : 337 pages
File Size : 49,5 Mb
Release : 2020-07-03
Category : Political Science
ISBN : 3030173143

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Big Data Science and Analytics for Smart Sustainable Urbanism by Simon Elias Bibri Pdf

We are living at the dawn of what has been termed ‘the fourth paradigm of science,’ a scientific revolution that is marked by both the emergence of big data science and analytics, and by the increasing adoption of the underlying technologies in scientific and scholarly research practices. Everything about science development or knowledge production is fundamentally changing thanks to the ever-increasing deluge of data. This is the primary fuel of the new age, which powerful computational processes or analytics algorithms are using to generate valuable knowledge for enhanced decision-making, and deep insights pertaining to a wide variety of practical uses and applications. This book addresses the complex interplay of the scientific, technological, and social dimensions of the city, and what it entails in terms of the systemic implications for smart sustainable urbanism. In concrete terms, it explores the interdisciplinary and transdisciplinary field of smart sustainable urbanism and the unprecedented paradigmatic shifts and practical advances it is undergoing in light of big data science and analytics. This new era of science and technology embodies an unprecedentedly transformative and constitutive power—manifested not only in the form of revolutionizing science and transforming knowledge, but also in advancing social practices, producing new discourses, catalyzing major shifts, and fostering societal transitions. Of particular relevance, it is instigating a massive change in the way both smart cities and sustainable cities are studied and understood, and in how they are planned, designed, operated, managed, and governed in the face of urbanization. This relates to what has been dubbed data-driven smart sustainable urbanism, an emerging approach based on a computational understanding of city systems and processes that reduces urban life to logical and algorithmic rules and procedures, while also harnessing urban big data to provide a more holistic and integrated view or synoptic intelligence of the city. This is increasingly being directed towards improving, advancing, and maintaining the contribution of both sustainable cities and smart cities to the goals of sustainable development. This timely and multifaceted book is aimed at a broad readership. As such, it will appeal to urban scientists, data scientists, urbanists, planners, engineers, designers, policymakers, philosophers of science, and futurists, as well as all readers interested in an overview of the pivotal role of big data science and analytics in advancing every academic discipline and social practice concerned with data–intensive science and its application, particularly in relation to sustainability.

Data Intensive Computing Applications for Big Data

M. Mittal,V.E. Balas,D.J. Hemanth
Data Intensive Computing Applications for Big Data Book PDF

Author : M. Mittal,V.E. Balas,D.J. Hemanth
Publisher : IOS Press
Page : 618 pages
File Size : 44,8 Mb
Release : 2018-01-31
Category : Computers
ISBN : 9781614998143

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Data Intensive Computing Applications for Big Data by M. Mittal,V.E. Balas,D.J. Hemanth Pdf

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.

Computing with Data

Guy Lebanon,Mohamed El-Geish
Computing with Data Book PDF

Author : Guy Lebanon,Mohamed El-Geish
Publisher : Springer
Page : 576 pages
File Size : 47,7 Mb
Release : 2018-11-28
Category : Computers
ISBN : 9783319981499

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Computing with Data by Guy Lebanon,Mohamed El-Geish Pdf

This book introduces basic computing skills designed for industry professionals without a strong computer science background. Written in an easily accessible manner, and accompanied by a user-friendly website, it serves as a self-study guide to survey data science and data engineering for those who aspire to start a computing career, or expand on their current roles, in areas such as applied statistics, big data, machine learning, data mining, and informatics. The authors draw from their combined experience working at software and social network companies, on big data products at several major online retailers, as well as their experience building big data systems for an AI startup. Spanning from the basic inner workings of a computer to advanced data manipulation techniques, this book opens doors for readers to quickly explore and enhance their computing knowledge. Computing with Data comprises a wide range of computational topics essential for data scientists, analysts, and engineers, providing them with the necessary tools to be successful in any role that involves computing with data. The introduction is self-contained, and chapters progress from basic hardware concepts to operating systems, programming languages, graphing and processing data, testing and programming tools, big data frameworks, and cloud computing. The book is fashioned with several audiences in mind. Readers without a strong educational background in CS--or those who need a refresher--will find the chapters on hardware, operating systems, and programming languages particularly useful. Readers with a strong educational background in CS, but without significant industry background, will find the following chapters especially beneficial: learning R, testing, programming, visualizing and processing data in Python and R, system design for big data, data stores, and software craftsmanship.

Data Science and Big Data Analytics

Durgesh Kumar Mishra,Xin-She Yang,Aynur Unal
Data Science and Big Data Analytics Book PDF

Author : Durgesh Kumar Mishra,Xin-She Yang,Aynur Unal
Publisher : Springer
Page : 406 pages
File Size : 42,5 Mb
Release : 2018-08-01
Category : Technology & Engineering
ISBN : 9789811076411

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Data Science and Big Data Analytics by Durgesh Kumar Mishra,Xin-She Yang,Aynur Unal Pdf

This book presents conjectural advances in big data analysis, machine learning and computational intelligence, as well as their potential applications in scientific computing. It discusses major issues pertaining to big data analysis using computational intelligence techniques, and the conjectural elements are supported by simulation and modelling applications to help address real-world problems. An extensive bibliography is provided at the end of each chapter. Further, the main content is supplemented by a wealth of figures, graphs, and tables, offering a valuable guide for researchers in the field of big data analytics and computational intelligence.