Disk Based Algorithms For Big Data
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Disk Based Algorithms For Big Data
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Author : Christopher Graham Healey
language : en
Publisher:
Release Date : 2017
Disk Based Algorithms For Big Data written by Christopher Graham Healey and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017 with Big data categories.
Disk Based Algorithms For Big Data
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Author : Christopher G. Healey
language : en
Publisher: CRC Press
Release Date : 2016-11-17
Disk Based Algorithms For Big Data written by Christopher G. Healey and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-11-17 with Mathematics categories.
Disk-Based Algorithms for Big Data is a product of recent advances in the areas of big data, data analytics, and the underlying file systems and data management algorithms used to support the storage and analysis of massive data collections. The book discusses hard disks and their impact on data management, since Hard Disk Drives continue to be common in large data clusters. It also explores ways to store and retrieve data though primary and secondary indices. This includes a review of different in-memory sorting and searching algorithms that build a foundation for more sophisticated on-disk approaches like mergesort, B-trees, and extendible hashing. Following this introduction, the book transitions to more recent topics, including advanced storage technologies like solid-state drives and holographic storage; peer-to-peer (P2P) communication; large file systems and query languages like Hadoop/HDFS, Hive, Cassandra, and Presto; and NoSQL databases like Neo4j for graph structures and MongoDB for unstructured document data. Designed for senior undergraduate and graduate students, as well as professionals, this book is useful for anyone interested in understanding the foundations and advances in big data storage and management, and big data analytics. About the Author Dr. Christopher G. Healey is a tenured Professor in the Department of Computer Science and the Goodnight Distinguished Professor of Analytics in the Institute for Advanced Analytics, both at North Carolina State University in Raleigh, North Carolina. He has published over 50 articles in major journals and conferences in the areas of visualization, visual and data analytics, computer graphics, and artificial intelligence. He is a recipient of the National Science Foundation’s CAREER Early Faculty Development Award and the North Carolina State University Outstanding Instructor Award. He is a Senior Member of the Association for Computing Machinery (ACM) and the Institute of Electrical and Electronics Engineers (IEEE), and an Associate Editor of ACM Transaction on Applied Perception, the leading worldwide journal on the application of human perception to issues in computer science.
Disk Based Algorithms For Big Data
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Author : Christopher Graham Healey
language : en
Publisher:
Release Date : 2016
Disk Based Algorithms For Big Data written by Christopher Graham Healey and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016 with Big data categories.
Data Science And Big Data An Environment Of Computational Intelligence
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Author : Witold Pedrycz
language : en
Publisher: Springer
Release Date : 2017-03-21
Data Science And Big Data An Environment Of Computational Intelligence written by Witold Pedrycz and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-03-21 with Technology & Engineering categories.
This book presents a comprehensive and up-to-date treatise of a range of methodological and algorithmic issues. It also discusses implementations and case studies, identifies the best design practices, and assesses data analytics business models and practices in industry, health care, administration and business.Data science and big data go hand in hand and constitute a rapidly growing area of research and have attracted the attention of industry and business alike. The area itself has opened up promising new directions of fundamental and applied research and has led to interesting applications, especially those addressing the immediate need to deal with large repositories of data and building tangible, user-centric models of relationships in data. Data is the lifeblood of today’s knowledge-driven economy.Numerous data science models are oriented towards end users and along with the regular requirements for accuracy (which are present in any modeling), come the requirements for ability to process huge and varying data sets as well as robustness, interpretability, and simplicity (transparency). Computational intelligence with its underlying methodologies and tools helps address data analytics needs.The book is of interest to those researchers and practitioners involved in data science, Internet engineering, computational intelligence, management, operations research, and knowledge-based systems.
Big Data In Action From Algorithms To Scalable Product Solutions 2025 Author 1 Dr Mehraj Ali Usman Ali
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Author : AUTHOR:1-Dr. Mehraj Ali Usman Ali, AUTHOR:2 -Dr. Shakeb Khan
language : en
Publisher: YASHITA PRAKASHAN PRIVATE LIMITED
Release Date :
Big Data In Action From Algorithms To Scalable Product Solutions 2025 Author 1 Dr Mehraj Ali Usman Ali written by AUTHOR:1-Dr. Mehraj Ali Usman Ali, AUTHOR:2 -Dr. Shakeb Khan and has been published by YASHITA PRAKASHAN PRIVATE LIMITED this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.
PREFACE In an era dominated by technological advancements, the ability to extract meaningful insights from the ever-expanding volume of data has become a competitive advantage for organizations worldwide. Big Data, with its vast scope, provides companies with unprecedented opportunities to understand consumer behavior, optimize operations, and forecast future trends. Yet, despite its potential, raw data alone is insufficient; it needs to be processed, analyzed, and interpreted in a way that yields actionable insights. This is where Predictive Analytics comes into play. Predictive analytics is the practice of using historical data, machine learning algorithms, and statistical models to forecast future outcomes and trends. By leveraging Big Data, predictive analytics allows organizations to anticipate future behaviors, market shifts, and operational needs with remarkable accuracy. This predictive power is transforming industries, from retail and healthcare to finance and manufacturing, by providing businesses with tools to make data-driven decisions rather than relying solely on intuition or past experience. The goal of this book is to explore the intersection of Big Data and Predictive Analytics, providing readers with both theoretical insights and practical approaches to harnessing predictive models in Big Data environments. Throughout the chapters, we will cover the various types of predictive models, including regression analysis, time-series forecasting, decision trees, and neural networks, highlighting how these models can be applied to Big Data to solve real-world challenges. These methodologies are essential for applications ranging from demand forecasting and fraud detection to personalized marketing and healthcare diagnostics. Data preparation plays a pivotal role in predictive analytics, and this book will delve into the critical process of cleaning, transforming, and normalizing Big Data to ensure accurate and reliable predictions. Additionally, we will explore the implementation of machine learning algorithms, such as supervised and unsupervised learning, which form the backbone of many predictive models used in modern business applications. One of the core themes of this book is to demonstrate how predictive analytics is not just a tool for data scientists but a crucial component of decision support systems, helping organizations make informed choices across various departments, including marketing, operations, and finance. The book will also address the challenges that come with predictive analytics, such as data quality, overfitting, and model interpretability, providing solutions to these common obstacles. Through detailed case studies, particularly in the financial, retail, and healthcare sectors, this book highlights the transformative impact of predictive analytics in Big Data. By the end of this book, readers will not only gain an understanding of the core principles of predictive analytics but will also be equipped with the knowledge to apply these techniques in their own organizations to drive meaningful business outcomes. We hope this book serves as both an academic resource and a practical guide, empowering professionals, researchers, and students to fully leverage predictive analytics in the context of Big Data. Authors Dr. Mehraj Ali Usman Ali Dr. Shakeb Khan
Business Intelligence And Big Data
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Author : Esteban Zimányi
language : en
Publisher: Springer
Release Date : 2018-07-14
Business Intelligence And Big Data written by Esteban Zimányi and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-07-14 with Computers categories.
This book constitutes revised tutorial lectures of the 7th European Business Intelligence and Big Data Summer School, eBISS 2017, held in Bruxelles, Belgium, in July 2017. The tutorials were given by renowned experts and covered advanced aspects of business intelligence and big data. This summer school, presented by leading researchers in the field, represented an opportunity for postgraduate students to equip themselves with the theoretical, practical, and collaboration skills necessary for developing challenging business intelligence applications.
Algorithms And Architectures For Parallel Processing
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Author : Meikang Qiu
language : en
Publisher: Springer Nature
Release Date : 2020-09-30
Algorithms And Architectures For Parallel Processing written by Meikang Qiu and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-09-30 with Mathematics categories.
This three-volume set LNCS 12452, 12453, and 12454 constitutes the proceedings of the 20th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2020, in New York City, NY, USA, in October 2020. The total of 142 full papers and 5 short papers included in this proceedings volumes was carefully reviewed and selected from 495 submissions. ICA3PP is covering the many dimensions of parallel algorithms and architectures, encompassing fundamental theoretical approaches, practical experimental projects, and commercial components and systems. As applications of computing systems have permeated in every aspects of daily life, the power of computing system has become increasingly critical. This conference provides a forum for academics and practitioners from countries around the world to exchange ideas for improving the efficiency, performance, reliability, security and interoperability of computing systems and applications. ICA3PP 2020 focus on two broad areas of parallel and distributed computing, i.e. architectures, algorithms and networks, and systems and applications.
Artificial Intelligence And Iot
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Author : Kalaiselvi Geetha Manoharan
language : en
Publisher: Springer Nature
Release Date : 2021-02-12
Artificial Intelligence And Iot written by Kalaiselvi Geetha Manoharan and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-02-12 with Technology & Engineering categories.
This book projects a futuristic scenario that is more existent than they have been at any time earlier. To be conscious of the bursting prospective of IoT, it has to be amalgamated with AI technologies. Predictive and advanced analysis can be made based on the data collected, discovered and analyzed. To achieve all these compatibility, complexity, legal and ethical issues arise due to automation of connected components and gadgets of widespread companies across the globe. While these are a few examples of issues, the authors’ intention in editing this book is to offer concepts of integrating AI with IoT in a precise and clear manner to the research community. In editing this book, the authors’ attempt is to provide novel advances and applications to address the challenge of continually discovering patterns for IoT by covering various aspects of implementing AI techniques to make IoT solutions smarter. The only way to remain pace with this data generated by the IoT and acquire the concealed acquaintance it encloses is to employ AI as the eventual catalyst for IoT. IoT together with AI is more than an inclination or existence; it will develop into a paradigm. It helps those researchers who have an interest in this field to keep insight into different concepts and their importance for applications in real life. This has been done to make the edited book more flexible and to stimulate further interest in topics. All these motivated the authors toward integrating AI in achieving smarter IoT. The authors believe that their effort can make this collection interesting and highly attract the student pursuing pre-research, research and even master in multidisciplinary domain.
Web And Big Data
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Author : Jie Shao
language : en
Publisher: Springer
Release Date : 2019-07-25
Web And Big Data written by Jie Shao and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-07-25 with Computers categories.
This two-volume set, LNCS 11641 and 11642, constitutes the thoroughly refereed proceedings of the Third International Joint Conference, APWeb-WAIM 2019, held in Chengdu, China, in August 2019. The 42 full papers presented together with 17 short papers, and 6 demonstration papers were carefully reviewed and selected from 180 submissions. The papers are organized around the following topics: Big Data Analytics; Data and Information Quality; Data Mining and Application; Graph Data and Social Networks; Information Extraction and Retrieval; Knowledge Graph; Machine Learning; Recommender Systems; Storage, Indexing and Physical Database Design; Spatial, Temporal and Multimedia Databases; Text Analysis and Mining; and Demo.
Advanced Hadoop Techniques A Comprehensive Guide To Mastery
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Author : Adam Jones
language : en
Publisher: Walzone Press
Release Date : 2025-05-13
Advanced Hadoop Techniques A Comprehensive Guide To Mastery written by Adam Jones and has been published by Walzone Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-13 with Computers categories.
Unlock the full potential of Hadoop with "Advanced Hadoop Techniques: A Comprehensive Guide to Mastery"—your essential resource for navigating the intricate complexities and harnessing the tremendous power of the Hadoop ecosystem. Designed for data engineers, developers, administrators, and data scientists, this book elevates your skills from foundational concepts to the most advanced optimizations necessary for mastery. Delve deep into the core of Hadoop, unraveling its integral components such as HDFS, MapReduce, and YARN, while expanding your knowledge to encompass critical ecosystem projects like Hive, HBase, Sqoop, and Spark. Through meticulous explanations and real-world examples, "Advanced Hadoop Techniques: A Comprehensive Guide to Mastery" equips you with the tools to efficiently deploy, manage, and optimize Hadoop clusters. Learn to fortify your Hadoop deployments by implementing robust security measures to ensure data protection and compliance. Discover the intricacies of performance tuning to significantly enhance your data processing and analytics capabilities. This book empowers you to not only learn Hadoop but to master sophisticated techniques that convert vast data sets into actionable insights. Perfect for aspiring professionals eager to make an impact in the realm of big data and seasoned experts aiming to refine their craft, "Advanced Hadoop Techniques: A Comprehensive Guide to Mastery" serves as an invaluable resource. Embark on your journey into the future of big data with confidence and expertise—your path to Hadoop mastery starts here.