November 26, 2020

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Data Analysis in the Cloud

Data Analysis in the Cloud
Author : Domenico Talia,Paolo Trunfio,Fabrizio Marozzo
Publisher : Elsevier
Release Date : 2015-09-15
Category : Computers
Total pages :150
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Data Analysis in the Cloud introduces and discusses models, methods, techniques, and systems to analyze the large number of digital data sources available on the Internet using the computing and storage facilities of the cloud. Coverage includes scalable data mining and knowledge discovery techniques together with cloud computing concepts, models, and systems. Specific sections focus on map-reduce and NoSQL models. The book also includes techniques for conducting high-performance distributed analysis of large data on clouds. Finally, the book examines research trends such as Big Data pervasive computing, data-intensive exascale computing, and massive social network analysis. Introduces data analysis techniques and cloud computing concepts Describes cloud-based models and systems for Big Data analytics Provides examples of the state-of-the-art in cloud data analysis Explains how to develop large-scale data mining applications on clouds Outlines the main research trends in the area of scalable Big Data analysis

Data Analysis in the Cloud

Data Analysis in the Cloud
Author : Domenico Talia,Paolo Trunfio,Fabrizio Marozzo
Publisher : Elsevier
Release Date : 2015-09-25
Category :
Total pages :150
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Data Analysis in the Cloud introduces and discusses models, methods, techniques, and systems to analyze the large number of digital data sources available on the Internet using the computing and storage facilities of the cloud. Coverage includes scalable data mining and knowledge discovery techniques together with cloud computing concepts, models, and systems. Specific sections focus on map-reduce and NoSQL models. The book also includes techniques for conducting high-performance distributed analysis of large data on clouds. Finally, the book examines research trends such as Big Data pervasive computing, data-intensive exascale computing, and massive social network analysis. Introduces data analysis techniques and cloud computing concepts Describes cloud-based models and systems for Big Data analytics Provides examples of the state-of-the-art in cloud data analysis Explains how to develop large-scale data mining applications on clouds Outlines the main research trends in the area of scalable Big Data analysis

Big-Data Analytics and Cloud Computing

Big-Data Analytics and Cloud Computing
Author : Marcello Trovati,Richard Hill,Ashiq Anjum,Shao Ying Zhu,Lu Liu
Publisher : Springer
Release Date : 2016-01-12
Category : Computers
Total pages :169
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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.

Cloud Computing for Geospatial Big Data Analytics

Cloud Computing for Geospatial Big Data Analytics
Author : Himansu Das,Rabindra K. Barik,Harishchandra Dubey,Diptendu Sinha Roy
Publisher : Springer
Release Date : 2018-12-11
Category : Computers
Total pages :289
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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.

Exam Prep for: Data Analysis in the Cloud

Exam Prep for: Data Analysis in the Cloud
Author : Anonim
Publisher : Unknown
Release Date : 2020
Category :
Total pages :129
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Communication, Cloud and Big Data

Communication, Cloud and Big Data
Author : Hiren Kumar Deva Sarma,Prativa Rai,Samarjeet Borah
Publisher : ACCB Publishing
Release Date : 2014-12-31
Category : Computers
Total pages :158
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Analysis of big data is becoming a hot stuff for engineers, researchers and business enterprises now a days. It refers to the process of collecting, organizing and analyzing large sets of data to discover hidden patterns and other useful information. Not solely can massive information analytics assist to know the knowledge contained inside the information, however it will additionally facilitate to determine the information that is most significant to the business and future business choices. Cloud computing is the type of computing that relies on sharing computing resources rather than having local servers or personal devices to handle applications. Cloud computing aims at applying traditional supercomputing, or high-performance computing power to perform tens of trillions of computations per second, in consumer-oriented applications such as financial portfolios, to deliver personalized information, to provide data storage etc. Since big data places on networks, storage and servers, requirements arise to analyse this huge amount data on the cloud. Even cloud providers also welcome this new business opportunity of supporting big data analysis in the cloud. But in the same time they are facing various, architectural and technical hurdles. Therefore, big data analysis in cloud attacting many researchers now a days. The National Conference on Communication, Cloud and Big Data (CCB) 2014 organized by Department of Information Technology, SMIT has received keen response from researchers across the country. Each paper went through reviews process and finally, 30 papers were selected for presentation. The papers are an even mix of research topics from the fields of Communication, Cloud and Big Data and its applications in various fields of engineering and science.

A Brief Survey on Smart Grid Data Analysis in the Cloud

A Brief Survey on Smart Grid Data Analysis in the Cloud
Author : Anonim
Publisher : Unknown
Release Date : 2020
Category :
Total pages :129
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Abstract: Cloud Computing has become more and more of a choice for storing and processing data due to the performance, scalability, availability and interoperability that it offers. The adoption of generic off-the-shelf Information and Communication Technologies (ICT) for the Smart Grid has come with many advantages, but also raised issues regarding the security, availability and reliability of the Smart Grid. The data generated by the Smart Grid's systems has the properties of a time series and its analysis needs to be secure and in real-time. As shown in this paper, cloud computing has become a real candidate for Smart Grid data analysis. We present the particularities of the data generated in the Smart Grid and the operations involved in its analysis. As well we compare existing solutions for stream data processing against this basic set of operations.

Big-Data Analytics for Cloud, IoT and Cognitive Computing

Big-Data Analytics for Cloud, IoT and Cognitive Computing
Author : Kai Hwang,Min Chen
Publisher : John Wiley & Sons
Release Date : 2017-03-17
Category : Computers
Total pages :432
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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.

Cloud-based Big Data Analytics in Vehicular Ad-hoc Networks

Cloud-based Big Data Analytics in Vehicular Ad-hoc Networks
Author : Ram Shringar Rao,Nanhay Singh,Omprakash Kaiwartya,Sanjoy Das
Publisher : Engineering Science Reference
Release Date : 2020
Category : Big data
Total pages :300
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"This book covers a range of new concepts in emerging VANETs including the integration with cloud computing and big data analytics, emerging wireless networking concepts, and computing models"--

Handbook of Research on Cloud Infrastructures for Big Data Analytics

Handbook of Research on Cloud Infrastructures for Big Data Analytics
Author : Raj, Pethuru
Publisher : IGI Global
Release Date : 2014-03-31
Category : Computers
Total pages :570
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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.

Advances in Big Data and Cloud Computing

Advances in Big Data and Cloud Computing
Author : Elijah Blessing Rajsingh,Jey Veerasamy,Amir H. Alavi,J. Dinesh Peter
Publisher : Springer
Release Date : 2018-04-06
Category : Technology & Engineering
Total pages :413
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This book is a compendium of the proceedings of the International Conference on Big-Data and Cloud Computing. It includes recent advances in the areas of big data analytics, cloud computing, the Internet of nano things, cloud security, data analytics in the cloud, smart cities and grids, etc. Primarily focusing on the application of knowledge that promotes ideas for solving the problems of the society through cutting-edge technologies, it provides novel ideas that further world-class research and development. This concise compilation of articles approved by a panel of expert reviewers is an invaluable resource for researchers in the area of advanced engineering sciences.

Cloud Computing for Data Analysis

Cloud Computing for Data Analysis
Author : Noah Gift
Publisher : Unknown
Release Date : 2020
Category :
Total pages :199
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This book is designed to give you a comprehensive view of cloud computing including Big Data and Machine Learning. Many resources will be used including interactive labs on Cloud Platforms (Google, AWS, Azure) using Python. This is a project-based book with extensive hands-on assignments. Based on material taught at leading universities.

Data Science on Google Cloud Platform: Exploratory Data Analytics

Data Science on Google Cloud Platform: Exploratory Data Analytics
Author : Kumaran Ponnambalam
Publisher : Unknown
Release Date : 2018
Category :
Total pages :129
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Strategic Engineering for Cloud Computing and Big Data Analytics

Strategic Engineering for Cloud Computing and Big Data Analytics
Author : Amin Hosseinian-Far,Muthu Ramachandran,Dilshad Sarwar
Publisher : Springer
Release Date : 2017-03-15
Category : Technology & Engineering
Total pages :226
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This book demonstrates the use of a wide range of strategic engineering concepts, theories and applied case studies to improve the safety, security and sustainability of complex and large-scale engineering and computer systems. It first details the concepts of system design, life cycle, impact assessment and security to show how these ideas can be brought to bear on the modeling, analysis and design of information systems with a focused view on cloud-computing systems and big data analytics. This informative book is a valuable resource for graduate students, researchers and industry-based practitioners working in engineering, information and business systems as well as strategy.

Cloud Computing and Big Data

Cloud Computing and Big Data
Author : C. Catlett,W. Gentzsch,L. Grandinetti
Publisher : IOS Press
Release Date : 2013-10-22
Category : Computers
Total pages :264
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Cloud computing offers many advantages to researchers and engineers who need access to high performance computing facilities for solving particular compute-intensive and/or large-scale problems, but whose overall high performance computing (HPC) needs do not justify the acquisition and operation of dedicated HPC facilities. There are, however, a number of fundamental problems which must be addressed, such as the limitations imposed by accessibility, security and communication speed, before these advantages can be exploited to the full. This book presents 14 contributions selected from the International Research Workshop on Advanced High Performance Computing Systems, held in Cetraro, Italy, in June 2012. The papers are arranged in three chapters. Chapter 1 includes five papers on cloud infrastructures, while Chapter 2 discusses cloud applications. The third chapter in the book deals with big data, which is nothing new – large scientific organizations have been collecting large amounts of data for decades – but what is new is that the focus has now broadened to include sectors such as business analytics, financial analyses, Internet service providers, oil and gas, medicine, automotive and a host of others. This book will be of interest to all those whose work involves them with aspects of cloud computing and big data applications.