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Techniques And Environments For Big Data Analysis


Techniques And Environments For Big Data Analysis
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Techniques And Environments For Big Data Analysis


Techniques And Environments For Big Data Analysis
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Author : B. S.P. Mishra
language : en
Publisher: Springer
Release Date : 2016-02-05

Techniques And Environments For Big Data Analysis written by B. S.P. Mishra and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-02-05 with Technology & Engineering categories.


This volume is aiming at a wide range of readers and researchers in the area of Big Data by presenting the recent advances in the fields of Big Data Analysis, as well as the techniques and tools used to analyze it. The book includes 10 distinct chapters providing a concise introduction to Big Data Analysis and recent Techniques and Environments for Big Data Analysis. It gives insight into how the expensive fitness evaluation of evolutionary learning can play a vital role in big data analysis by adopting Parallel, Grid, and Cloud computing environments.



Data Science And Big Data Analytics In Smart Environments


Data Science And Big Data Analytics In Smart Environments
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Author : Marta Chinnici
language : en
Publisher: CRC Press
Release Date : 2021-07-28

Data Science And Big Data Analytics In Smart Environments written by Marta Chinnici and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-07-28 with Computers categories.


Most applications generate large datasets, like social networking and social influence programs, smart cities applications, smart house environments, Cloud applications, public web sites, scientific experiments and simulations, data warehouse, monitoring platforms, and e-government services. Data grows rapidly, since applications produce continuously increasing volumes of both unstructured and structured data. Large-scale interconnected systems aim to aggregate and efficiently exploit the power of widely distributed resources. In this context, major solutions for scalability, mobility, reliability, fault tolerance and security are required to achieve high performance and to create a smart environment. The impact on data processing, transfer and storage is the need to re-evaluate the approaches and solutions to better answer the user needs. A variety of solutions for specific applications and platforms exist so a thorough and systematic analysis of existing solutions for data science, data analytics, methods and algorithms used in Big Data processing and storage environments is significant in designing and implementing a smart environment. Fundamental issues pertaining to smart environments (smart cities, ambient assisted leaving, smart houses, green houses, cyber physical systems, etc.) are reviewed. Most of the current efforts still do not adequately address the heterogeneity of different distributed systems, the interoperability between them, and the systems resilience. This book will primarily encompass practical approaches that promote research in all aspects of data processing, data analytics, data processing in different type of systems: Cluster Computing, Grid Computing, Peer-to-Peer, Cloud/Edge/Fog Computing, all involving elements of heterogeneity, having a large variety of tools and software to manage them. The main role of resource management techniques in this domain is to create the suitable frameworks for development of applications and deployment in smart environments, with respect to high performance. The book focuses on topics covering algorithms, architectures, management models, high performance computing techniques and large-scale distributed systems.



Big Data Fundamentals


Big Data Fundamentals
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Author : Thomas Erl
language : en
Publisher: Prentice Hall
Release Date : 2015-12-29

Big Data Fundamentals written by Thomas Erl and has been published by Prentice Hall this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-12-29 with Computers categories.


“This text should be required reading for everyone in contemporary business.” --Peter Woodhull, CEO, Modus21 “The one book that clearly describes and links Big Data concepts to business utility.” --Dr. Christopher Starr, PhD “Simply, this is the best Big Data book on the market!” --Sam Rostam, Cascadian IT Group “...one of the most contemporary approaches I’ve seen to Big Data fundamentals...” --Joshua M. Davis, PhD The Definitive Plain-English Guide to Big Data for Business and Technology Professionals Big Data Fundamentals provides a pragmatic, no-nonsense introduction to Big Data. Best-selling IT author Thomas Erl and his team clearly explain key Big Data concepts, theory and terminology, as well as fundamental technologies and techniques. All coverage is supported with case study examples and numerous simple diagrams. The authors begin by explaining how Big Data can propel an organization forward by solving a spectrum of previously intractable business problems. Next, they demystify key analysis techniques and technologies and show how a Big Data solution environment can be built and integrated to offer competitive advantages. Discovering Big Data’s fundamental concepts and what makes it different from previous forms of data analysis and data science Understanding the business motivations and drivers behind Big Data adoption, from operational improvements through innovation Planning strategic, business-driven Big Data initiatives Addressing considerations such as data management, governance, and security Recognizing the 5 “V” characteristics of datasets in Big Data environments: volume, velocity, variety, veracity, and value Clarifying Big Data’s relationships with OLTP, OLAP, ETL, data warehouses, and data marts Working with Big Data in structured, unstructured, semi-structured, and metadata formats Increasing value by integrating Big Data resources with corporate performance monitoring Understanding how Big Data leverages distributed and parallel processing Using NoSQL and other technologies to meet Big Data’s distinct data processing requirements Leveraging statistical approaches of quantitative and qualitative analysis Applying computational analysis methods, including machine learning



Big Data Analytics Techniques For Market Intelligence


Big Data Analytics Techniques For Market Intelligence
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Author : Darwish, Dina
language : en
Publisher: IGI Global
Release Date : 2024-01-04

Big Data Analytics Techniques For Market Intelligence written by Darwish, Dina and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-01-04 with Computers categories.


The ever-expanding realm of Big Data poses a formidable challenge for academic scholars and professionals due to the sheer magnitude and diversity of data types, along with the continuous influx of information from various sources. Extracting valuable insights from this vast and complex dataset is crucial for organizations to uncover market intelligence and make informed decisions. However, without the proper guidance and understanding of Big Data analytics techniques and methodologies, scholars may struggle to navigate this landscape and maximize the potential benefits of their research. In response to this pressing need, Professor Dina Darwish presents Big Data Analytics Techniques for Market Intelligence, a groundbreaking book that addresses the specific challenges faced by scholars and professionals in the field. Through a comprehensive exploration of various techniques and methodologies, this book offers a solution to the hurdles encountered in extracting meaningful information from Big Data. Covering the entire lifecycle of Big Data analytics, including preprocessing, analysis, visualization, and utilization of results, the book equips readers with the knowledge and tools necessary to unlock the power of Big Data and generate valuable market intelligence. With real-world case studies and a focus on practical guidance, scholars and professionals can effectively leverage Big Data analytics to drive strategic decision-making and stay at the forefront of this rapidly evolving field.



Data Science And Big Data An Environment Of Computational Intelligence


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.



Tenth International Conference On Applications And Techniques In Cyber Intelligence Icatci 2022


Tenth International Conference On Applications And Techniques In Cyber Intelligence Icatci 2022
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Author : Jemal H. Abawajy
language : en
Publisher: Springer Nature
Release Date : 2023-03-29

Tenth International Conference On Applications And Techniques In Cyber Intelligence Icatci 2022 written by Jemal H. Abawajy and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-03-29 with Computers categories.


This book presents innovative ideas, cutting-edge findings, and novel techniques, methods, and applications in a broad range of cybersecurity and cyberthreat intelligence areas. As our society becomes smarter, there is a corresponding need to secure our cyberfuture. The book describes approaches and findings that are of interest to business professionals and governments seeking to secure our data and underpin infrastructures, as well as to individual users.



Computational And Statistical Methods For Analysing Big Data With Applications


Computational And Statistical Methods For Analysing Big Data With Applications
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Author : Shen Liu
language : en
Publisher: Academic Press
Release Date : 2015-11-20

Computational And Statistical Methods For Analysing Big Data With Applications written by Shen Liu and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-11-20 with Mathematics categories.


Due to the scale and complexity of data sets currently being collected in areas such as health, transportation, environmental science, engineering, information technology, business and finance, modern quantitative analysts are seeking improved and appropriate computational and statistical methods to explore, model and draw inferences from big data. This book aims to introduce suitable approaches for such endeavours, providing applications and case studies for the purpose of demonstration. Computational and Statistical Methods for Analysing Big Data with Applications starts with an overview of the era of big data. It then goes onto explain the computational and statistical methods which have been commonly applied in the big data revolution. For each of these methods, an example is provided as a guide to its application. Five case studies are presented next, focusing on computer vision with massive training data, spatial data analysis, advanced experimental design methods for big data, big data in clinical medicine, and analysing data collected from mobile devices, respectively. The book concludes with some final thoughts and suggested areas for future research in big data. - Advanced computational and statistical methodologies for analysing big data are developed - Experimental design methodologies are described and implemented to make the analysis of big data more computationally tractable - Case studies are discussed to demonstrate the implementation of the developed methods - Five high-impact areas of application are studied: computer vision, geosciences, commerce, healthcare and transportation - Computing code/programs are provided where appropriate



Big Data


Big Data
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Author : Kuan-Ching Li
language : en
Publisher: CRC Press
Release Date : 2015-02-23

Big Data written by Kuan-Ching Li and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-02-23 with Computers categories.


As today's organizations are capturing exponentially larger amounts of data than ever, now is the time for organizations to rethink how they digest that data. Through advanced algorithms and analytics techniques, organizations can harness this data, discover hidden patterns, and use the newly acquired knowledge to achieve competitive advantages.Pre



Predictive Analytics Data Mining And Big Data


Predictive Analytics Data Mining And Big Data
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Author : S. Finlay
language : en
Publisher: Springer
Release Date : 2014-07-01

Predictive Analytics Data Mining And Big Data written by S. Finlay and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-07-01 with Business & Economics categories.


This in-depth guide provides managers with a solid understanding of data and data trends, the opportunities that it can offer to businesses, and the dangers of these technologies. Written in an accessible style, Steven Finlay provides a contextual roadmap for developing solutions that deliver benefits to organizations.



Data And Information In Online Environments


Data And Information In Online Environments
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Author : Rogério Mugnaini
language : en
Publisher: Springer Nature
Release Date : 2020-06-15

Data And Information In Online Environments written by Rogério Mugnaini and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-15 with Computers categories.


This book constitutes the refereed post-conference proceedings of the First International Conference on Data and Information in Online Environments, DIONE 2020, which took place in Florianópolis, Brazil, in March 2020. DIONE 2020 handles the growing interaction between the information sciences, communication sciences and computer sciences. The 18 revised full papers were carefully reviewed and selected from 37 submissions and focus on the production, dissemination and evaluation of contents in online environments. The goal is to improve cooperation between data science, natural language processing, data engineering, big data, research evaluation, network science, sociology of science and communication communities.