Distributed Computing in Big Data Analytics

Distributed Computing in Big Data Analytics
Author: Sourav Mazumder,Robin Singh Bhadoria,Ganesh Chandra Deka
Publsiher: Springer
Total Pages: 162
Release: 2017-08-29
ISBN: 3319598341
Category: Computers
Language: EN, FR, DE, ES & NL

Distributed Computing in Big Data Analytics Book Excerpt:

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 for Sustainable Computing

Big Data Analytics for Sustainable Computing
Author: Haldorai, Anandakumar,Ramu, Arulmurugan
Publsiher: IGI Global
Total Pages: 263
Release: 2019-09-20
ISBN: 1522597522
Category: Computers
Language: EN, FR, DE, ES & NL

Big Data Analytics for Sustainable Computing 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.

Big Data Analytics Systems Algorithms Applications

Big Data Analytics  Systems  Algorithms  Applications
Author: C.S.R. Prabhu,Aneesh Sreevallabh Chivukula,Aditya Mogadala,Rohit Ghosh,L.M. Jenila Livingston
Publsiher: Springer Nature
Total Pages: 412
Release: 2019-10-14
ISBN: 9811500940
Category: Computers
Language: EN, FR, DE, ES & NL

Big Data Analytics Systems Algorithms Applications Book Excerpt:

This book provides a comprehensive survey of techniques, technologies and applications of Big Data and its analysis. The Big Data phenomenon is increasingly impacting all sectors of business and industry, producing an emerging new information ecosystem. On the applications front, the book offers detailed descriptions of various application areas for Big Data Analytics in the important domains of Social Semantic Web Mining, Banking and Financial Services, Capital Markets, Insurance, Advertisement, Recommendation Systems, Bio-Informatics, the IoT and Fog Computing, before delving into issues of security and privacy. With regard to machine learning techniques, the book presents all the standard algorithms for learning – including supervised, semi-supervised and unsupervised techniques such as clustering and reinforcement learning techniques to perform collective Deep Learning. Multi-layered and nonlinear learning for Big Data are also covered. In turn, the book highlights real-life case studies on successful implementations of Big Data Analytics at large IT companies such as Google, Facebook, LinkedIn and Microsoft. Multi-sectorial case studies on domain-based companies such as Deutsche Bank, the power provider Opower, Delta Airlines and a Chinese City Transportation application represent a valuable addition. Given its comprehensive coverage of Big Data Analytics, the book offers a unique resource for undergraduate and graduate students, researchers, educators and IT professionals alike.

Big Data Concepts Methodologies Tools and Applications

Big Data  Concepts  Methodologies  Tools  and Applications
Author: Management Association, Information Resources
Publsiher: IGI Global
Total Pages: 2478
Release: 2016-04-20
ISBN: 1466698411
Category: Computers
Language: EN, FR, DE, ES & NL

Big Data Concepts Methodologies Tools and Applications Book Excerpt:

The digital age has presented an exponential growth in the amount of data available to individuals looking to draw conclusions based on given or collected information across industries. Challenges associated with the analysis, security, sharing, storage, and visualization of large and complex data sets continue to plague data scientists and analysts alike as traditional data processing applications struggle to adequately manage big data. Big Data: Concepts, Methodologies, Tools, and Applications is a multi-volume compendium of research-based perspectives and solutions within the realm of large-scale and complex data sets. Taking a multidisciplinary approach, this publication presents exhaustive coverage of crucial topics in the field of big data including diverse applications, storage solutions, analysis techniques, and methods for searching and transferring large data sets, in addition to security issues. Emphasizing essential research in the field of data science, this publication is an ideal reference source for data analysts, IT professionals, researchers, and academics.

Big Data Management Technologies and Applications

Big Data Management  Technologies  and Applications
Author: Hu, Wen-Chen
Publsiher: IGI Global
Total Pages: 342
Release: 2013-10-31
ISBN: 1466647000
Category: Computers
Language: EN, FR, DE, ES & NL

Big Data Management Technologies and Applications Book Excerpt:

"This book discusses the exponential growth of information size and the innovative methods for data capture, storage, sharing, and analysis for big data"--Provided by publisher.

Big Data Analytics for Sensor Network Collected Intelligence

Big Data Analytics for Sensor Network Collected Intelligence
Author: Hui-Huang Hsu,Chuan-Yu Chang,Ching-Hsien Hsu
Publsiher: Morgan Kaufmann
Total Pages: 326
Release: 2017-02-02
ISBN: 012809625X
Category: Computers
Language: EN, FR, DE, ES & NL

Big Data Analytics for Sensor Network Collected Intelligence Book Excerpt:

Big Data Analytics for Sensor-Network Collected Intelligence explores state-of-the-art methods for using advanced ICT technologies to perform intelligent analysis on sensor collected data. The book shows how to develop systems that automatically detect natural and human-made events, how to examine people’s behaviors, and how to unobtrusively provide better services. It begins by exploring big data architecture and platforms, covering the cloud computing infrastructure and how data is stored and visualized. The book then explores how big data is processed and managed, the key security and privacy issues involved, and the approaches used to ensure data quality. In addition, readers will find a thorough examination of big data analytics, analyzing statistical methods for data analytics and data mining, along with a detailed look at big data intelligence, ubiquitous and mobile computing, and designing intelligence system based on context and situation. Indexing: The books of this series are submitted to EI-Compendex and SCOPUS Contains contributions from noted scholars in computer science and electrical engineering from around the globe Provides a broad overview of recent developments in sensor collected intelligence Edited by a team comprised of leading thinkers in big data analytics

Social Data Analytics

Social Data Analytics
Author: Amin Beheshti,Samira Ghodratnama,Mehdi Elahi,Helia Farhood
Publsiher: CRC Press
Total Pages: 250
Release: 2022-08-01
ISBN: 100064460X
Category: Business & Economics
Language: EN, FR, DE, ES & NL

Social Data Analytics Book Excerpt:

This book is an introduction to social data analytics along with its challenges and opportunities in the age of Big Data and Artificial Intelligence. It focuses primarily on concepts, techniques and methods for organizing, curating, processing, analyzing, and visualizing big social data: from text to image and video analytics. It provides novel techniques in storytelling with social data to facilitate the knowledge and fact discovery. The book covers a large body of knowledge that will help practitioners and researchers in understanding the underlying concepts, problems, methods, tools and techniques involved in modern social data analytics. It also provides real-world applications of social data analytics, including: Sales and Marketing, Influence Maximization, Situational Awareness, customer success and Segmentation, and performance analysis of the industry. It provides a deep knowledge in social data analytics by comprehensively classifying the current state of research, by describing in-depth techniques and methods, and by highlighting future research directions. Lecturers will find a wealth of material to choose from for a variety of courses, ranging from undergraduate courses in data science to graduate courses in data analytics.

Big Data Analytics for Cloud IoT and Cognitive Computing

Big Data Analytics for Cloud  IoT and Cognitive Computing
Author: Kai Hwang,Min Chen
Publsiher: John Wiley & Sons
Total Pages: 432
Release: 2017-03-13
ISBN: 1119247047
Category: Computers
Language: EN, FR, DE, ES & NL

Big Data Analytics for Cloud IoT and Cognitive Computing 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.

Distributed Computing in Java 9

Distributed Computing in Java 9
Author: Raja Malleswara Rao Pattamsetti
Publsiher: Packt Publishing Ltd
Total Pages: 304
Release: 2017-06-30
ISBN: 1787122735
Category: Computers
Language: EN, FR, DE, ES & NL

Distributed Computing in Java 9 Book Excerpt:

Explore the power of distributed computing to write concurrent, scalable applications in Java About This Book Make the best of Java 9 features to write succinct code Handle large amounts of data using HPC Make use of AWS and Google App Engine along with Java to establish a powerful remote computation system Who This Book Is For This book is for basic to intermediate level Java developers who is aware of object-oriented programming and Java basic concepts. What You Will Learn Understand the basic concepts of parallel and distributed computing/programming Achieve performance improvement using parallel processing, multithreading, concurrency, memory sharing, and hpc cluster computing Get an in-depth understanding of Enterprise Messaging concepts with Java Messaging Service and Web Services in the context of Enterprise Integration Patterns Work with Distributed Database technologies Understand how to develop and deploy a distributed application on different cloud platforms including Amazon Web Service and Docker CaaS Concepts Explore big data technologies Effectively test and debug distributed systems Gain thorough knowledge of security standards for distributed applications including two-way Secure Socket Layer In Detail Distributed computing is the concept with which a bigger computation process is accomplished by splitting it into multiple smaller logical activities and performed by diverse systems, resulting in maximized performance in lower infrastructure investment. This book will teach you how to improve the performance of traditional applications through the usage of parallelism and optimized resource utilization in Java 9. After a brief introduction to the fundamentals of distributed and parallel computing, the book moves on to explain different ways of communicating with remote systems/objects in a distributed architecture. You will learn about asynchronous messaging with enterprise integration and related patterns, and how to handle large amount of data using HPC and implement distributed computing for databases. Moving on, it explains how to deploy distributed applications on different cloud platforms and self-contained application development. You will also learn about big data technologies and understand how they contribute to distributed computing. The book concludes with the detailed coverage of testing, debugging, troubleshooting, and security aspects of distributed applications so the programs you build are robust, efficient, and secure. Style and approach This is a step-by-step practical guide with real-world examples.

Cognitive Computing and Big Data Analytics

Cognitive Computing and Big Data Analytics
Author: Judith S. Hurwitz,Marcia Kaufman,Adrian Bowles
Publsiher: John Wiley & Sons
Total Pages: 288
Release: 2015-04-08
ISBN: 1118896785
Category: Computers
Language: EN, FR, DE, ES & NL

Cognitive Computing and Big Data Analytics Book Excerpt:

A comprehensive guide to learning technologies that unlock thevalue in big data Cognitive Computing provides detailed guidance towardbuilding a new class of systems that learn from experience andderive insights to unlock the value of big data. This book helpstechnologists understand cognitive computing's underlyingtechnologies, from knowledge representation techniques and naturallanguage processing algorithms to dynamic learning approaches basedon accumulated evidence, rather than reprogramming. Detailed caseexamples from the financial, healthcare, and manufacturing walkreaders step-by-step through the design and testing of cognitivesystems, and expert perspectives from organizations such asCleveland Clinic, Memorial Sloan-Kettering, as well as commercialvendors that are creating solutions. These organizations provideinsight into the real-world implementation of cognitive computingsystems. The IBM Watson cognitive computing platform is describedin a detailed chapter because of its significance in helping todefine this emerging market. In addition, the book includesimplementations of emerging projects from Qualcomm, Hitachi, Googleand Amazon. Today's cognitive computing solutions build on establishedconcepts from artificial intelligence, natural language processing,ontologies, and leverage advances in big data management andanalytics. They foreshadow an intelligent infrastructure thatenables a new generation of customer and context-aware smartapplications in all industries. Cognitive Computing is a comprehensive guide to thesubject, providing both the theoretical and practical guidancetechnologists need. Discover how cognitive computing evolved from promise toreality Learn the elements that make up a cognitive computingsystem Understand the groundbreaking hardware and softwaretechnologies behind cognitive computing Learn to evaluate your own application portfolio to find thebest candidates for pilot projects Leverage cognitive computing capabilities to transform theorganization Cognitive systems are rightly being hailed as the new era ofcomputing. Learn how these technologies enable emerging firms tocompete with entrenched giants, and forward-thinking establishedfirms to disrupt their industries. Professionals who currently workwith big data and analytics will see how cognitive computing buildson their foundation, and creates new opportunities. CognitiveComputing provides complete guidance to this new level ofhuman-machine interaction.

Big Data Analytics in Cybersecurity

Big Data Analytics in Cybersecurity
Author: Onur Savas,Julia Deng
Publsiher: CRC Press
Total Pages: 336
Release: 2017-09-18
ISBN: 1351650416
Category: Business & Economics
Language: EN, FR, DE, ES & NL

Big Data Analytics in Cybersecurity Book Excerpt:

Big data is presenting challenges to cybersecurity. For an example, the Internet of Things (IoT) will reportedly soon generate a staggering 400 zettabytes (ZB) of data a year. Self-driving cars are predicted to churn out 4000 GB of data per hour of driving. Big data analytics, as an emerging analytical technology, offers the capability to collect, store, process, and visualize these vast amounts of data. Big Data Analytics in Cybersecurity examines security challenges surrounding big data and provides actionable insights that can be used to improve the current practices of network operators and administrators. Applying big data analytics in cybersecurity is critical. By exploiting data from the networks and computers, analysts can discover useful network information from data. Decision makers can make more informative decisions by using this analysis, including what actions need to be performed, and improvement recommendations to policies, guidelines, procedures, tools, and other aspects of the network processes. Bringing together experts from academia, government laboratories, and industry, the book provides insight to both new and more experienced security professionals, as well as data analytics professionals who have varying levels of cybersecurity expertise. It covers a wide range of topics in cybersecurity, which include: Network forensics Threat analysis Vulnerability assessment Visualization Cyber training. In addition, emerging security domains such as the IoT, cloud computing, fog computing, mobile computing, and cyber-social networks are examined. The book first focuses on how big data analytics can be used in different aspects of cybersecurity including network forensics, root-cause analysis, and security training. Next it discusses big data challenges and solutions in such emerging cybersecurity domains as fog computing, IoT, and mobile app security. The book concludes by presenting the tools and datasets for future cybersecurity research.

Big Data Analytics with Hadoop 3

Big Data Analytics with Hadoop 3
Author: Sridhar Alla
Publsiher: Packt Publishing Ltd
Total Pages: 482
Release: 2018-05-31
ISBN: 1788624955
Category: Computers
Language: EN, FR, DE, ES & NL

Big Data Analytics with Hadoop 3 Book Excerpt:

Explore big data concepts, platforms, analytics, and their applications using the power of Hadoop 3 Key Features Learn Hadoop 3 to build effective big data analytics solutions on-premise and on cloud Integrate Hadoop with other big data tools such as R, Python, Apache Spark, and Apache Flink Exploit big data using Hadoop 3 with real-world examples Book Description Apache Hadoop is the most popular platform for big data processing, and can be combined with a host of other big data tools to build powerful analytics solutions. Big Data Analytics with Hadoop 3 shows you how to do just that, by providing insights into the software as well as its benefits with the help of practical examples. Once you have taken a tour of Hadoop 3’s latest features, you will get an overview of HDFS, MapReduce, and YARN, and how they enable faster, more efficient big data processing. You will then move on to learning how to integrate Hadoop with the open source tools, such as Python and R, to analyze and visualize data and perform statistical computing on big data. As you get acquainted with all this, you will explore how to use Hadoop 3 with Apache Spark and Apache Flink for real-time data analytics and stream processing. In addition to this, you will understand how to use Hadoop to build analytics solutions on the cloud and an end-to-end pipeline to perform big data analysis using practical use cases. By the end of this book, you will be well-versed with the analytical capabilities of the Hadoop ecosystem. You will be able to build powerful solutions to perform big data analytics and get insight effortlessly. What you will learn Explore the new features of Hadoop 3 along with HDFS, YARN, and MapReduce Get well-versed with the analytical capabilities of Hadoop ecosystem using practical examples Integrate Hadoop with R and Python for more efficient big data processing Learn to use Hadoop with Apache Spark and Apache Flink for real-time data analytics Set up a Hadoop cluster on AWS cloud Perform big data analytics on AWS using Elastic Map Reduce Who this book is for Big Data Analytics with Hadoop 3 is for you if you are looking to build high-performance analytics solutions for your enterprise or business using Hadoop 3’s powerful features, or you’re new to big data analytics. A basic understanding of the Java programming language is required.

Computational Intelligence Applications in Business Intelligence and Big Data Analytics

Computational Intelligence Applications in Business Intelligence and Big Data Analytics
Author: Vijayan Sugumaran,Arun Kumar Sangaiah,Arunkumar Thangavelu
Publsiher: CRC Press
Total Pages: 362
Release: 2017-06-26
ISBN: 1351720252
Category: Computers
Language: EN, FR, DE, ES & NL

Computational Intelligence Applications in Business Intelligence and Big Data Analytics Book Excerpt:

There are a number of books on computational intelligence (CI), but they tend to cover a broad range of CI paradigms and algorithms rather than provide an in-depth exploration in learning and adaptive mechanisms. This book sets its focus on CI based architectures, modeling, case studies and applications in big data analytics, and business intelligence. The intended audiences of this book are scientists, professionals, researchers, and academicians who deal with the new challenges and advances in the specific areas mentioned above. Designers and developers of applications in these areas can learn from other experts and colleagues through this book.

Data Analytics with Hadoop

Data Analytics with Hadoop
Author: Benjamin Bengfort,Jenny Kim
Publsiher: "O'Reilly Media, Inc."
Total Pages: 288
Release: 2016-06
ISBN: 1491913762
Category: Computers
Language: EN, FR, DE, ES & NL

Data Analytics with Hadoop Book Excerpt:

Ready to use statistical and machine-learning techniques across large data sets? This practical guide shows you why the Hadoop ecosystem is perfect for the job. Instead of deployment, operations, or software development usually associated with distributed computing, you’ll focus on particular analyses you can build, the data warehousing techniques that Hadoop provides, and higher order data workflows this framework can produce. Data scientists and analysts will learn how to perform a wide range of techniques, from writing MapReduce and Spark applications with Python to using advanced modeling and data management with Spark MLlib, Hive, and HBase. You’ll also learn about the analytical processes and data systems available to build and empower data products that can handle—and actually require—huge amounts of data. Understand core concepts behind Hadoop and cluster computing Use design patterns and parallel analytical algorithms to create distributed data analysis jobs Learn about data management, mining, and warehousing in a distributed context using Apache Hive and HBase Use Sqoop and Apache Flume to ingest data from relational databases Program complex Hadoop and Spark applications with Apache Pig and Spark DataFrames Perform machine learning techniques such as classification, clustering, and collaborative filtering with Spark’s MLlib

Intelligent Distributed Computing VI

Intelligent Distributed Computing VI
Author: Giancarlo Fortino,Costin Badica,Michele Malgeri,Rainer Unland
Publsiher: Springer
Total Pages: 318
Release: 2012-08-22
ISBN: 3642325246
Category: Technology & Engineering
Language: EN, FR, DE, ES & NL

Intelligent Distributed Computing VI Book Excerpt:

This book represents the combined peer-reviewed proceedings of the Sixth International Symposium on Intelligent Distributed Computing -- IDC~2012, of the International Workshop on Agents for Cloud -- A4C~2012 and of the Fourth International Workshop on Multi-Agent Systems Technology and Semantics -- MASTS~2012. All the events were held in Calabria, Italy during September 24-26, 2012. The 37 contributions published in this book address many topics related to theory and applications of intelligent distributed computing and multi-agent systems, including: adaptive and autonomous distributed systems, agent programming, ambient assisted living systems, business process modeling and verification, cloud computing, coalition formation, decision support systems, distributed optimization and constraint satisfaction, gesture recognition, intelligent energy management in WSNs, intelligent logistics, machine learning, mobile agents, parallel and distributed computational intelligence, parallel evolutionary computing, trust metrics and security, scheduling in distributed heterogenous computing environments, semantic Web service composition, social simulation, and software agents for WSNs.

Distributed Computing and Internet Technology

Distributed Computing and Internet Technology
Author: Atul Negi,Raj Bhatnagar,Laxmi Parida
Publsiher: Springer
Total Pages: 343
Release: 2018-01-03
ISBN: 3319723448
Category: Computers
Language: EN, FR, DE, ES & NL

Distributed Computing and Internet Technology Book Excerpt:

This book constitutes the proceedings of the 14th International Conference on Distributed Computing and Internet Technology, ICDCIT 2018, held in Bhubaneswar, India, in January 2018. The 9 full papers, 11 short papers and 3 poster papers presented in this book were carefully reviewed and selected from 120 submissions. The ICDCIT conference focusses on security and privacy; distributed and multiprocessing approaches; networks protocols and applications; and databases, algorithms, data processing and applications.

Handbook of Research on Cloud Infrastructures for Big Data Analytics

Handbook of Research on Cloud Infrastructures for Big Data Analytics
Author: Raj, Pethuru
Publsiher: IGI Global
Total Pages: 570
Release: 2014-03-31
ISBN: 1466658657
Category: Computers
Language: EN, FR, DE, ES & NL

Handbook of Research on Cloud Infrastructures for Big Data Analytics 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.

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

Emerging Trends in IoT and Integration with Data Science  Cloud Computing  and Big Data Analytics
Author: Taser, Pelin Yildirim
Publsiher: IGI Global
Total Pages: 334
Release: 2021-11-05
ISBN: 1799841871
Category: Computers
Language: EN, FR, DE, ES & NL

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

New Frontiers in High Performance Computing and Big Data

New Frontiers in High Performance Computing and Big Data
Author: G. Fox,V. Getov,L. Grandinetti
Publsiher: IOS Press
Total Pages: 272
Release: 2017-11-14
ISBN: 1614998167
Category: Computers
Language: EN, FR, DE, ES & NL

New Frontiers in High Performance Computing and Big Data Book Excerpt:

For the last four decades, parallel computing platforms have increasingly formed the basis for the development of high performance systems primarily aimed at the solution of intensive computing problems, and the application of parallel computing systems has also become a major factor in furthering scientific research. But such systems also offer the possibility of solving the problems encountered in the processing of large-scale scientific data sets, as well as in the analysis of Big Data in the fields of medicine, social media, marketing, economics etc. This book presents papers from the International Research Workshop on Advanced High Performance Computing Systems, held in Cetraro, Italy, in July 2016. The workshop covered a wide range of topics and new developments related to the solution of intensive and large-scale computing problems, and the contributions included in this volume cover aspects of the evolution of parallel platforms and highlight some of the problems encountered with the development of ever more powerful computing systems. The importance of future large-scale data science applications is also discussed. The book will be of particular interest to all those involved in the development or application of parallel computing systems.

Big Data Analytics and Cloud Computing

Big Data Analytics and Cloud Computing
Author: Marcello Trovati,Richard Hill,Ashiq Anjum,Shao Ying Zhu,Lu Liu
Publsiher: Springer
Total Pages: 169
Release: 2016-01-12
ISBN: 3319253131
Category: Computers
Language: EN, FR, DE, ES & NL

Big Data Analytics and Cloud Computing 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.