Processing Analysing Large Computer Data Streams Using Big Data

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Processing Analysing Large Computer Data Streams Using Big Data

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Author : Dr. Ashad Ullah Qureshi
language : en
Publisher: Concepts Books Publication
Release Date : 2022-06-01

Processing Analysing Large Computer Data Streams Using Big Data written by Dr. Ashad Ullah Qureshi and has been published by Concepts Books Publication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-01 with Computers categories.

The emerging large datasets have made efficient data processing a much more difficult task for the traditional methodologies. Invariably, datasets continue to increase rapidly in size with time. The purpose of this research is to give an overview of some of the tools and techniques that can be utilized to manage and analyze large datasets. We propose a faster way to catalogue and retrieve data by creating a directory file – more specifically, an improved method that would allow file retrieval based on its time and date. This method eliminates the process of searching the entire content of files and reduces the time it takes to locate the selected data. We also implement the nearest search algorithm in an event where the searched query is not found. The algorithm sorts through data to find the closest points that are within close proximity to the searched query. We also offer an efficient data reduction method that effectively condenses the amount of data. The algorithm enables users to store the desired amount of data in a file and decrease the time in which observations are retrieved for processing. This is achieved by using a reduced standard deviation range to minimize the original data and keeping the dataset to a significant smaller dataset size.

Large Scale And Big Data

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Author : Sherif Sakr
language : en
Publisher: CRC Press
Release Date : 2014-06-25

Large Scale And Big Data written by Sherif Sakr and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-06-25 with Computers categories.

Large Scale and Big Data: Processing and Management provides readers with a central source of reference on the data management techniques currently available for large-scale data processing. Presenting chapters written by leading researchers, academics, and practitioners, it addresses the fundamental challenges associated with Big Data processing t

Applied Data Science

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Author : Martin Braschler
language : en
Publisher: Springer
Release Date : 2019-06-13

Applied Data Science written by Martin Braschler and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-06-13 with Computers categories.

This book has two main goals: to define data science through the work of data scientists and their results, namely data products, while simultaneously providing the reader with relevant lessons learned from applied data science projects at the intersection of academia and industry. As such, it is not a replacement for a classical textbook (i.e., it does not elaborate on fundamentals of methods and principles described elsewhere), but systematically highlights the connection between theory, on the one hand, and its application in specific use cases, on the other. With these goals in mind, the book is divided into three parts: Part I pays tribute to the interdisciplinary nature of data science and provides a common understanding of data science terminology for readers with different backgrounds. These six chapters are geared towards drawing a consistent picture of data science and were predominantly written by the editors themselves. Part II then broadens the spectrum by presenting views and insights from diverse authors – some from academia and some from industry, ranging from financial to health and from manufacturing to e-commerce. Each of these chapters describes a fundamental principle, method or tool in data science by analyzing specific use cases and drawing concrete conclusions from them. The case studies presented, and the methods and tools applied, represent the nuts and bolts of data science. Finally, Part III was again written from the perspective of the editors and summarizes the lessons learned that have been distilled from the case studies in Part II. The section can be viewed as a meta-study on data science across a broad range of domains, viewpoints and fields. Moreover, it provides answers to the question of what the mission-critical factors for success in different data science undertakings are. The book targets professionals as well as students of data science:first, practicing data scientists in industry and academia who want to broaden their scope and expand their knowledge by drawing on the authors’ combined experience. Second, decision makers in businesses who face the challenge of creating or implementing a data-driven strategy and who want to learn from success stories spanning a range of industries. Third, students of data science who want to understand both the theoretical and practical aspects of data science, vetted by real-world case studies at the intersection of academia and industry.

Data Science And Big Data Computing

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Author : Zaigham Mahmood
language : en
Publisher: Springer
Release Date : 2016-07-05

Data Science And Big Data Computing written by Zaigham Mahmood and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-07-05 with Business & Economics categories.

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.

Statistical Analysis Of Massive Data Streams

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Author :
language : en
Publisher: National Academies Press
Release Date : 2004

Statistical Analysis Of Massive Data Streams written by and has been published by National Academies Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with Computers categories.

Massive data streams, large quantities of data that arrive continuously, are becoming increasingly commonplace in many areas of science and technology. Consequently development of analytical methods for such streams is of growing importance. To address this issue, the National Security Agency asked the NRC to hold a workshop to explore methods for analysis of streams of data so as to stimulate progress in the field. This report presents the results of that workshop. It provides presentations that focused on five different research areas where massive data streams are present: atmospheric and meteorological data; high-energy physics; integrated data systems; network traffic; and mining commercial data streams. The goals of the report are to improve communication among researchers in the field and to increase relevant statistical science activity.

Big Data Preprocessing

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Author : Julián Luengo
language : en
Publisher: Springer Nature
Release Date : 2020-03-16

Big Data Preprocessing written by Julián Luengo and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-03-16 with Computers categories.

This book offers a comprehensible overview of Big Data Preprocessing, which includes a formal description of each problem. It also focuses on the most relevant proposed solutions. This book illustrates actual implementations of algorithms that helps the reader deal with these problems. This book stresses the gap that exists between big, raw data and the requirements of quality data that businesses are demanding. This is called Smart Data, and to achieve Smart Data the preprocessing is a key step, where the imperfections, integration tasks and other processes are carried out to eliminate superfluous information. The authors present the concept of Smart Data through data preprocessing in Big Data scenarios and connect it with the emerging paradigms of IoT and edge computing, where the end points generate Smart Data without completely relying on the cloud. Finally, this book provides some novel areas of study that are gathering a deeper attention on the Big Data preprocessing. Specifically, it considers the relation with Deep Learning (as of a technique that also relies in large volumes of data), the difficulty of finding the appropriate selection and concatenation of preprocessing techniques applied and some other open problems. Practitioners and data scientists who work in this field, and want to introduce themselves to preprocessing in large data volume scenarios will want to purchase this book. Researchers that work in this field, who want to know which algorithms are currently implemented to help their investigations, may also be interested in this book.

Research Anthology On Big Data Analytics Architectures And Applications

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Author : Management Association, Information Resources
language : en
Publisher: IGI Global
Release Date : 2021-09-24

Research Anthology On Big Data Analytics Architectures And Applications written by Management Association, Information Resources and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-24 with Computers categories.

Society is now completely driven by data with many industries relying on data to conduct business or basic functions within the organization. With the efficiencies that big data bring to all institutions, data is continuously being collected and analyzed. However, data sets may be too complex for traditional data-processing, and therefore, different strategies must evolve to solve the issue. The field of big data works as a valuable tool for many different industries. The Research Anthology on Big Data Analytics, Architectures, and Applications is a complete reference source on big data analytics that offers the latest, innovative architectures and frameworks and explores a variety of applications within various industries. Offering an international perspective, the applications discussed within this anthology feature global representation. Covering topics such as advertising curricula, driven supply chain, and smart cities, this research anthology is ideal for data scientists, data analysts, computer engineers, software engineers, technologists, government officials, managers, CEOs, professors, graduate students, researchers, and academicians.

Open Source Software For Statistical Analysis Of Big Data Emerging Research And Opportunities

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Author : Segall, Richard S.
language : en
Publisher: IGI Global
Release Date : 2020-02-21

Open Source Software For Statistical Analysis Of Big Data Emerging Research And Opportunities written by Segall, Richard S. and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-02-21 with Computers categories.

With the development of computing technologies in today’s modernized world, software packages have become easily accessible. Open source software, specifically, is a popular method for solving certain issues in the field of computer science. One key challenge is analyzing big data due to the high amounts that organizations are processing. Researchers and professionals need research on the foundations of open source software programs and how they can successfully analyze statistical data. Open Source Software for Statistical Analysis of Big Data: Emerging Research and Opportunities provides emerging research exploring the theoretical and practical aspects of cost-free software possibilities for applications within data analysis and statistics with a specific focus on R and Python. Featuring coverage on a broad range of topics such as cluster analysis, time series forecasting, and machine learning, this book is ideally designed for researchers, developers, practitioners, engineers, academicians, scholars, and students who want to more fully understand in a brief and concise format the realm and technologies of open source software for big data and how it has been used to solve large-scale research problems in a multitude of disciplines.

Data Warehousing In The Age Of Big Data

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Author : Krish Krishnan
language : en
Publisher: Newnes
Release Date : 2013-05-02

Data Warehousing In The Age Of Big Data written by Krish Krishnan and has been published by Newnes this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-05-02 with Computers categories.

Data Warehousing in the Age of the Big Data will help you and your organization make the most of unstructured data with your existing data warehouse. As Big Data continues to revolutionize how we use data, it doesn't have to create more confusion. Expert author Krish Krishnan helps you make sense of how Big Data fits into the world of data warehousing in clear and concise detail. The book is presented in three distinct parts. Part 1 discusses Big Data, its technologies and use cases from early adopters. Part 2 addresses data warehousing, its shortcomings, and new architecture options, workloads, and integration techniques for Big Data and the data warehouse. Part 3 deals with data governance, data visualization, information life-cycle management, data scientists, and implementing a Big Data–ready data warehouse. Extensive appendixes include case studies from vendor implementations and a special segment on how we can build a healthcare information factory. Ultimately, this book will help you navigate through the complex layers of Big Data and data warehousing while providing you information on how to effectively think about using all these technologies and the architectures to design the next-generation data warehouse. - Learn how to leverage Big Data by effectively integrating it into your data warehouse. - Includes real-world examples and use cases that clearly demonstrate Hadoop, NoSQL, HBASE, Hive, and other Big Data technologies - Understand how to optimize and tune your current data warehouse infrastructure and integrate newer infrastructure matching data processing workloads and requirements

Broadband Communications Networks And Systems

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Author : Wei Xiang
language : en
Publisher: Springer Nature
Release Date : 2022-01-01

Broadband Communications Networks And Systems written by Wei Xiang and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-01-01 with Computers categories.

This book constitutes the refereed post-conference proceedings of the 12th International Conference on Broadband Communications, Networks, and Systems, Broadnets 2021, which took place in October 2021. Due to COVID-19 pandemic the conference was held virtually. The 24 full papers presented were carefully reviewed and selected from 49 submissions. The papers are thematically grouped as a session on broadband communications, networks, and systems; 5G-enabled smart building: technology and challenge; and 5G: The advances in industry.