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Big Data Analytics Techniques Tools And Applications


Big Data Analytics Techniques Tools And Applications
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Big Data Analytics Techniques Tools And Applications


Big Data Analytics Techniques Tools And Applications
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Author : HEMANT SINGH SENGAR SAURABH ASHWINIKUMAR DAVE BALACHANDAR RAMALINGAM OM GOEL
language : en
Publisher: DeepMisti Publication
Release Date : 2024-10-18

Big Data Analytics Techniques Tools And Applications written by HEMANT SINGH SENGAR SAURABH ASHWINIKUMAR DAVE BALACHANDAR RAMALINGAM OM GOEL and has been published by DeepMisti Publication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-18 with Computers categories.


In the ever-evolving landscape of the modern world, the synergy between technology and management has become a cornerstone of innovation and progress. This book, Big Data Analytics: Techniques, Tools, and Applications, is conceived to bridge the gap between emerging technological advancements in data analytics and their strategic application across industries. Our objective is to equip readers with the tools and insights necessary to excel in this dynamic intersection of fields. This book is structured to provide a comprehensive exploration of the methodologies and strategies that define the innovation of big data technologies and their integration into business practices. From foundational theories to advanced applications, we delve into the critical aspects that drive successful innovation in data-driven environments. We have made a concerted effort to present complex concepts in a clear and accessible manner, making this work suitable for a diverse audience, including students, managers, and industry professionals. In authoring this book, we have drawn upon the latest research and best practices to ensure that readers not only gain a robust theoretical understanding but also acquire practical skills that can be applied in real-world scenarios. The chapters are designed to strike a balance between depth and breadth, covering topics ranging from technological development and big data adoption to the strategic management of innovation. Additionally, we emphasize the importance of effective communication, dedicating sections to the art of presenting innovative ideas and solutions in a precise and academically rigorous manner. The inspiration for this book arises from a recognition of the crucial role that big data analytics and management play in shaping the future of businesses. We are profoundly grateful to Chancellor Shri Shiv Kumar Gupta of Maharaja Agrasen Himalayan Garhwal University for his unwavering support and vision. His dedication to fostering academic excellence and promoting a culture of innovation has been instrumental in bringing this project to fruition. We hope this book will serve as a valuable resource and inspiration for those eager to deepen their understanding of how big data technologies can be harnessed to drive innovation. We believe that the knowledge and insights contained within these pages will empower readers to lead the way in creating innovative solutions that will define the future of data-driven enterprises. Thank you for joining us on this journey. Authors



Big Data In Cardiology Predicting Preventing And Managing Diseases


Big Data In Cardiology Predicting Preventing And Managing Diseases
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Author : Bikal Dhungel
language : en
Publisher: GRIN Verlag
Release Date : 2020-10-28

Big Data In Cardiology Predicting Preventing And Managing Diseases written by Bikal Dhungel and has been published by GRIN Verlag this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-10-28 with Medical categories.


Master's Thesis from the year 2020 in the subject Health Sciences - Health Logistics, grade: 1,7, Linnaeus University (School of Informatics), course: Information Systems, language: English, abstract: This study was conducted to analyze this process closer focusing on a case of Cardiology. Conducting a comprehensive literature review and qualitative expert interviews, the impact of big data in the field of Cardiology was explored. The result of the study shows that big data can play a positive role in three aspects: prediction of disease, prevention of disease and management of disease. Big data enables us to build models that can be used to predict the occurrence of disease. Based on this information, actions can be taken to prevent the disease. Data also helps to manage the disease by offering helpful insights. Medical personnel can retrieve the patient data, with the help of AI, they can make faster decisions allowing them to spend more quality time with the patients and reduce cognitive errors. Through the interviews, it was understood that even though the positive role of big data has been acknowledged, the implementation is still a challenge due to various limitations. The challenges lie mainly on technical know-how and domain knowledge. Further challenges were data security and privacy issues that need to be addressed to mitigate the risks that can be caused by them. The examples of big data implementation in various cases like in heart failure prediction or prevention shows a positive picture. The overwhelming majority of case studies analyzed in this regard show an optimistic picture. Due to growing importance and use of smart devices, IoT, genomics and the recent developments in the field of ICTs, it is expected that big data will not only leave a positive influence on the field of Cardiology, it will also change the way medicine is practiced and healthcare is offered. The statement ‘Data is the new oil’ has been broadly acknowledged due to its wide-ranging importance. Utilizing big data offers a variety of benefits. Although the health sector was late in terms of exploiting the benefits of big data, currently, the adoption is accelerating. Healthcare is increasingly becoming an information science and the implementation of electronic medical records (EMR) and other information systems is growing rapidly. The patient data originating from smart devices and other sources like genomic databases are supporting the healthcare sector offering better healthcare delivery and increasing efficiency, hence saving costs.



Big Data Analytics Systems Algorithms Applications


Big Data Analytics Systems Algorithms Applications
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Author : C.S.R. Prabhu
language : en
Publisher: Springer Nature
Release Date : 2019-10-14

Big Data Analytics Systems Algorithms Applications written by C.S.R. Prabhu and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-14 with Computers categories.


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.



Computer And Information Technology


Computer And Information Technology
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Author : Prasad Yarlagadda
language : en
Publisher: Trans Tech Publications Ltd
Release Date : 2014-02-06

Computer And Information Technology written by Prasad Yarlagadda and has been published by Trans Tech Publications Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-02-06 with Technology & Engineering categories.


Selected, peer reviewed papers from the International Forum on Computer and Information Technology (IFCIT 2013), December 24-25, 2013, Shenzhen, China



Applied Machine Learning


Applied Machine Learning
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Author : M. Gopal
language : en
Publisher: McGraw Hill Professional
Release Date : 2019-06-07

Applied Machine Learning written by M. Gopal and has been published by McGraw Hill Professional this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-06-07 with Technology & Engineering categories.


Cutting-edge machine learning principles, practices, and applications This comprehensive textbook explores the theoretical under¬pinnings of learning and equips readers with the knowledge needed to apply powerful machine learning techniques to solve challenging real-world problems. Applied Machine Learning shows, step by step, how to conceptualize problems, accurately represent data, select and tune algorithms, interpret and analyze results, and make informed strategic decisions. Presented in a non-rigorous mathematical style, the book covers a broad array of machine learning topics with special emphasis on methods that have been profitably employed. Coverage includes: Supervised learning Statistical learning Learning with support vector machines (SVM) Learning with neural networks (NN) Fuzzy inference systems Data clustering Data transformations Decision tree learning Business intelligence Data mining And much more



Understanding Big Data Analytics For Enterprise Class Hadoop And Streaming Data


Understanding Big Data Analytics For Enterprise Class Hadoop And Streaming Data
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Author : IBM Paul Zikopoulos
language : en
Publisher: McGraw Hill Professional
Release Date : 2011-10-19

Understanding Big Data Analytics For Enterprise Class Hadoop And Streaming Data written by IBM Paul Zikopoulos and has been published by McGraw Hill Professional this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-10-19 with Computers categories.


Big Data represents a new era in data exploration and utilization, and IBM is uniquely positioned to help clients navigate this transformation. This book reveals how IBM is leveraging open source Big Data technology, infused with IBM technologies, to deliver a robust, secure, highly available, enterprise-class Big Data platform. The three defining characteristics of Big Data--volume, variety, and velocity--are discussed. You'll get a primer on Hadoop and how IBM is hardening it for the enterprise, and learn when to leverage IBM InfoSphere BigInsights (Big Data at rest) and IBM InfoSphere Streams (Big Data in motion) technologies. Industry use cases are also included in this practical guide. Learn how IBM hardens Hadoop for enterprise-class scalability and reliability Gain insight into IBM's unique in-motion and at-rest Big Data analytics platform Learn tips and tricks for Big Data use cases and solutions Get a quick Hadoop primer



Real Time Analytics


Real Time Analytics
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Author : Byron Ellis
language : en
Publisher: John Wiley & Sons
Release Date : 2014-07-21

Real Time Analytics written by Byron Ellis and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-07-21 with Computers categories.


Construct a robust end-to-end solution for analyzing and visualizing streaming data Real-time analytics is the hottest topic in data analytics today. In Real-Time Analytics: Techniques to Analyze and Visualize Streaming Data, expert Byron Ellis teaches data analysts technologies to build an effective real-time analytics platform. This platform can then be used to make sense of the constantly changing data that is beginning to outpace traditional batch-based analysis platforms. The author is among a very few leading experts in the field. He has a prestigious background in research, development, analytics, real-time visualization, and Big Data streaming and is uniquely qualified to help you explore this revolutionary field. Moving from a description of the overall analytic architecture of real-time analytics to using specific tools to obtain targeted results, Real-Time Analytics leverages open source and modern commercial tools to construct robust, efficient systems that can provide real-time analysis in a cost-effective manner. The book includes: A deep discussion of streaming data systems and architectures Instructions for analyzing, storing, and delivering streaming data Tips on aggregating data and working with sets Information on data warehousing options and techniques Real-Time Analytics includes in-depth case studies for website analytics, Big Data, visualizing streaming and mobile data, and mining and visualizing operational data flows. The book's "recipe" layout lets readers quickly learn and implement different techniques. All of the code examples presented in the book, along with their related data sets, are available on the companion website.



Data Science And Big Data Analytics


Data Science And Big Data Analytics
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Author : EMC Education Services
language : en
Publisher: John Wiley & Sons
Release Date : 2014-12-19

Data Science And Big Data Analytics written by EMC Education Services and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-12-19 with Computers categories.


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!



Social Big Data Analytics


Social Big Data Analytics
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Author : Bilal Abu-Salih
language : en
Publisher: Springer Nature
Release Date : 2021-03-10

Social Big Data Analytics written by Bilal Abu-Salih and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-03-10 with Business & Economics categories.


This book focuses on data and how modern business firms use social data, specifically Online Social Networks (OSNs) incorporated as part of the infrastructure for a number of emerging applications such as personalized recommendation systems, opinion analysis, expertise retrieval, and computational advertising. This book identifies how in such applications, social data offers a plethora of benefits to enhance the decision making process. This book highlights that business intelligence applications are more focused on structured data; however, in order to understand and analyse the social big data, there is a need to aggregate data from various sources and to present it in a plausible format. Big Social Data (BSD) exhibit all the typical properties of big data: wide physical distribution, diversity of formats, non-standard data models, independently-managed and heterogeneous semantics but even further valuable with marketing opportunities. The book provides a review of the current state-of-the-art approaches for big social data analytics as well as to present dissimilar methods to infer value from social data. The book further examines several areas of research that benefits from the propagation of the social data. In particular, the book presents various technical approaches that produce data analytics capable of handling big data features and effective in filtering out unsolicited data and inferring a value. These approaches comprise advanced technical solutions able to capture huge amounts of generated data, scrutinise the collected data to eliminate unwanted data, measure the quality of the inferred data, and transform the amended data for further data analysis. Furthermore, the book presents solutions to derive knowledge and sentiments from BSD and to provide social data classification and prediction. The approaches in this book also incorporate several technologies such as semantic discovery, sentiment analysis, affective computing and machine learning. This book has additional special feature enriched with numerous illustrations such as tables, graphs and charts incorporating advanced visualisation tools in accessible an attractive display.



Big Data Analytics


Big Data Analytics
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Author : Arun K. Somani
language : en
Publisher: CRC Press
Release Date : 2017-10-30

Big Data Analytics written by Arun K. Somani and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-10-30 with Computers categories.


The proposed book will discuss various aspects of big data Analytics. It will deliberate upon the tools, technology, applications, use cases and research directions in the field. Chapters would be contributed by researchers, scientist and practitioners from various reputed universities and organizations for the benefit of readers.