Big Data And Data Science
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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.
Big Data And Data Science
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Author : Dhaanyalakshmi Ahuja
language : en
Publisher: Educohack Press
Release Date : 2025-01-03
Big Data And Data Science written by Dhaanyalakshmi Ahuja and has been published by Educohack Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-03 with Computers categories.
Big Data and Data Science: Analytics for the Future dives into the fundamentals of big data and data science. We explain the data science life cycle and its major components, such as statistics and visualization, using various programming languages like R. As technology evolves, the significance of data science and big data analytics continues to grow, making this field increasingly important. Our book is designed in a reader-friendly manner, targeting newcomers to data science. Concepts are presented clearly and can be easily implemented through the procedures and algorithms provided. As data collection multiplies exponentially, analytics remains an evolving field with vast career opportunities. We cater to two types of readers: those skeptical about the benefits of big data and predictive analytics, and enthusiasts keen to explore current applications of these technologies. Big data is a fantastic choice for launching a career in IT, and this book equips you with the knowledge needed to succeed. We cover a broad spectrum of topics, ensuring a strong foundation in data science and big data analytics.
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.
Big Data Demystified
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Author : David Stephenson
language : en
Publisher: FT Press
Release Date : 2018-02-12
Big Data Demystified written by David Stephenson and has been published by FT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-02-12 with categories.
Big Data is a big topic, based on simple principles. Guided by leading expert in the field, David Stephenson, you will be amazed at how you can transform your company, and significantly improve KPIs across a broad range of business units and applications. Find out how an ecommerce company avoided two million product returns per year, how a newspaper saw triple-digit annual growth in digital subscriptions, how researchers in England learned to better detect pending cardiovascular problems, and how AI programs taught themselves to win games using techniques that even their human programmers didn't understand, all thanks to big data. Find out also how one company realized it could swap a million dollar hardware system with a twenty thousand dollar replacement. With simple and straightforward chapters that allow you to map examples onto your own business, Big Data Demystified will help you: · Know which data is most useful to collect now and why it's important to start collecting that data as soon as possible. · Understand big data and data science and how they can help you reach your business goals and gain competitive advantage. · Use big data to understand where you are now and how you can improve in the future. · Understand factors in choosing a big data system, including whether to go with cloud-based solutions. · Construct your big data team in a way that supports an effective strategy and helps make your business more data-driven. BIG DATA MAKES A BIG DIFFERENCE "Read this book! It is an essential guide to using data in a practical way that drives results." Ian McHenry, CEO Beyond Pricing "This is the book we've been missing: big data explained without the complexity." Marc Salomon, Professor in Decision Sciences and Dean at University of Amsterdam Business School "Big Data for the rest of us! I have never come across a book that is so full of practical advice, actionable examples and helpful explanations. Read this one book and start executing Big Data at your workplace tomorrow!" Tobias Wann CEO at @Leisure Group
Data Science And Big Data Analytics
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Author : Durgesh Kumar Mishra
language : en
Publisher: Springer
Release Date : 2018-08-01
Data Science And Big Data Analytics written by Durgesh Kumar Mishra and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-08-01 with Technology & Engineering categories.
This book presents conjectural advances in big data analysis, machine learning and computational intelligence, as well as their potential applications in scientific computing. It discusses major issues pertaining to big data analysis using computational intelligence techniques, and the conjectural elements are supported by simulation and modelling applications to help address real-world problems. An extensive bibliography is provided at the end of each chapter. Further, the main content is supplemented by a wealth of figures, graphs, and tables, offering a valuable guide for researchers in the field of big data analytics and computational intelligence.
Big Data Analytics And Data Science
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Author : Vikrant Bhateja
language : en
Publisher: Springer Nature
Release Date : 2024-12-23
Big Data Analytics And Data Science written by Vikrant Bhateja and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-23 with Computers categories.
This book presents a collection of high-quality, peer-reviewed research papers from the 8th International Conference on Information System Design and Intelligent Applications (ISDIA 2024), held in Dubai, UAE, from 3 - 4 January 2024. It covers a wide range of topics in computer science and information technology, including data mining and data warehousing, high-performance computing, parallel and distributed computing, computational intelligence, soft computing, big data, cloud computing, grid computing, cognitive computing, and information security.
Big Data Science And Analytics For Smart Sustainable Urbanism
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Author : Simon Elias Bibri
language : en
Publisher: Springer
Release Date : 2019-05-30
Big Data Science And Analytics For Smart Sustainable Urbanism written by Simon Elias Bibri and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-05-30 with Social Science categories.
We are living at the dawn of what has been termed ‘the fourth paradigm of science,’ a scientific revolution that is marked by both the emergence of big data science and analytics, and by the increasing adoption of the underlying technologies in scientific and scholarly research practices. Everything about science development or knowledge production is fundamentally changing thanks to the ever-increasing deluge of data. This is the primary fuel of the new age, which powerful computational processes or analytics algorithms are using to generate valuable knowledge for enhanced decision-making, and deep insights pertaining to a wide variety of practical uses and applications. This book addresses the complex interplay of the scientific, technological, and social dimensions of the city, and what it entails in terms of the systemic implications for smart sustainable urbanism. In concrete terms, it explores the interdisciplinary and transdisciplinary field of smart sustainable urbanism and the unprecedented paradigmatic shifts and practical advances it is undergoing in light of big data science and analytics. This new era of science and technology embodies an unprecedentedly transformative and constitutive power—manifested not only in the form of revolutionizing science and transforming knowledge, but also in advancing social practices, producing new discourses, catalyzing major shifts, and fostering societal transitions. Of particular relevance, it is instigating a massive change in the way both smart cities and sustainable cities are studied and understood, and in how they are planned, designed, operated, managed, and governed in the face of urbanization. This relates to what has been dubbed data-driven smart sustainable urbanism, an emerging approach based on a computational understanding of city systems and processes that reduces urban life to logical and algorithmic rules and procedures, while also harnessing urban big data to provide a more holisticand integrated view or synoptic intelligence of the city. This is increasingly being directed towards improving, advancing, and maintaining the contribution of both sustainable cities and smart cities to the goals of sustainable development. This timely and multifaceted book is aimed at a broad readership. As such, it will appeal to urban scientists, data scientists, urbanists, planners, engineers, designers, policymakers, philosophers of science, and futurists, as well as all readers interested in an overview of the pivotal role of big data science and analytics in advancing every academic discipline and social practice concerned with data–intensive science and its application, particularly in relation to sustainability.
Practical Big Data Analytics
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Author : Nataraj Dasgupta
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-01-15
Practical Big Data Analytics written by Nataraj Dasgupta and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-01-15 with Computers categories.
Get command of your organizational Big Data using the power of data science and analytics Key Features A perfect companion to boost your Big Data storing, processing, analyzing skills to help you take informed business decisions Work with the best tools such as Apache Hadoop, R, Python, and Spark for NoSQL platforms to perform massive online analyses Get expert tips on statistical inference, machine learning, mathematical modeling, and data visualization for Big Data Book Description Big Data analytics relates to the strategies used by organizations to collect, organize and analyze large amounts of data to uncover valuable business insights that otherwise cannot be analyzed through traditional systems. Crafting an enterprise-scale cost-efficient Big Data and machine learning solution to uncover insights and value from your organization's data is a challenge. Today, with hundreds of new Big Data systems, machine learning packages and BI Tools, selecting the right combination of technologies is an even greater challenge. This book will help you do that. With the help of this guide, you will be able to bridge the gap between the theoretical world of technology with the practical ground reality of building corporate Big Data and data science platforms. You will get hands-on exposure to Hadoop and Spark, build machine learning dashboards using R and R Shiny, create web-based apps using NoSQL databases such as MongoDB and even learn how to write R code for neural networks. By the end of the book, you will have a very clear and concrete understanding of what Big Data analytics means, how it drives revenues for organizations, and how you can develop your own Big Data analytics solution using different tools and methods articulated in this book. What you will learn - Get a 360-degree view into the world of Big Data, data science and machine learning - Broad range of technical and business Big Data analytics topics that caters to the interests of the technical experts as well as corporate IT executives - Get hands-on experience with industry-standard Big Data and machine learning tools such as Hadoop, Spark, MongoDB, KDB+ and R - Create production-grade machine learning BI Dashboards using R and R Shiny with step-by-step instructions - Learn how to combine open-source Big Data, machine learning and BI Tools to create low-cost business analytics applications - Understand corporate strategies for successful Big Data and data science projects - Go beyond general-purpose analytics to develop cutting-edge Big Data applications using emerging technologies Who this book is for The book is intended for existing and aspiring Big Data professionals who wish to become the go-to person in their organization when it comes to Big Data architecture, analytics, and governance. While no prior knowledge of Big Data or related technologies is assumed, it will be helpful to have some programming experience.
Big Data Data Mining And Data Science
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Author : George Dimitoglou
language : en
Publisher: Walter de Gruyter GmbH & Co KG
Release Date : 2024-12-30
Big Data Data Mining And Data Science written by George Dimitoglou and has been published by Walter de Gruyter GmbH & Co KG this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-30 with Computers categories.
Through the application of cutting-edge techniques like Big Data, Data Mining, and Data Science, it is possible to extract insights from massive datasets. These methodologies are crucial in enabling informed decision-making and driving transformative advancements across many fields, industries, and domains. This book offers an overview of latest tools, methods and approaches while also highlighting their practical use through various applications and case studies.
Data Science And Big Data Analytics
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Author : EMC Education Services
language : en
Publisher: John Wiley & Sons
Release Date : 2015-01-05
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 2015-01-05 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!