Big Data And Analytics
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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
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 Big Analytics
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Author : Michael Minelli
language : en
Publisher: John Wiley & Sons
Release Date : 2012-12-27
Big Data Big Analytics written by Michael Minelli 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 2012-12-27 with Business & Economics categories.
Unique prospective on the big data analytics phenomenon for both business and IT professionals The availability of Big Data, low-cost commodity hardware and new information management and analytics software has produced a unique moment in the history of business. The convergence of these trends means that we have the capabilities required to analyze astonishing data sets quickly and cost-effectively for the first time in history. These capabilities are neither theoretical nor trivial. They represent a genuine leap forward and a clear opportunity to realize enormous gains in terms of efficiency, productivity, revenue and profitability. The Age of Big Data is here, and these are truly revolutionary times. This timely book looks at cutting-edge companies supporting an exciting new generation of business analytics. Learn more about the trends in big data and how they are impacting the business world (Risk, Marketing, Healthcare, Financial Services, etc.) Explains this new technology and how companies can use them effectively to gather the data that they need and glean critical insights Explores relevant topics such as data privacy, data visualization, unstructured data, crowd sourcing data scientists, cloud computing for big data, and much more.
High Performance Big Data Analytics
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Author : Pethuru Raj
language : en
Publisher: Springer
Release Date : 2015-10-16
High Performance Big Data Analytics written by Pethuru Raj and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-10-16 with Computers categories.
This book presents a detailed review of high-performance computing infrastructures for next-generation big data and fast data analytics. Features: includes case studies and learning activities throughout the book and self-study exercises in every chapter; presents detailed case studies on social media analytics for intelligent businesses and on big data analytics (BDA) in the healthcare sector; describes the network infrastructure requirements for effective transfer of big data, and the storage infrastructure requirements of applications which generate big data; examines real-time analytics solutions; introduces in-database processing and in-memory analytics techniques for data mining; discusses the use of mainframes for handling real-time big data and the latest types of data management systems for BDA; provides information on the use of cluster, grid and cloud computing systems for BDA; reviews the peer-to-peer techniques and tools and the common information visualization techniques, used in BDA.
People Analytics In The Era Of Big Data
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Author : Jean Paul Isson
language : en
Publisher: John Wiley & Sons
Release Date : 2016-04-25
People Analytics In The Era Of Big Data written by Jean Paul Isson 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 2016-04-25 with Business & Economics categories.
Apply predictive analytics throughout all stages of workforce management People Analytics in the Era of Big Data provides a blueprint for leveraging your talent pool through the use of data analytics. Written by the Global Vice President of Business Intelligence and Predictive Analytics at Monster Worldwide, this book is packed full of actionable insights to help you source, recruit, acquire, engage, retain, promote, and manage the exceptional talent your organization needs. With a unique approach that applies analytics to every stage of the hiring process and the entire workforce planning and management cycle, this informative guide provides the key perspective that brings analytics into HR in a truly useful way. You're already inundated with disparate employee data, so why not mine that data for insights that add value to your organization and strengthen your workforce? This book presents a practical framework for real-world talent analytics, backed by groundbreaking examples of workforce analytics in action across the U.S., Canada, Europe, Asia, and Australia. Leverage predictive analytics throughout the hiring process Utilize analytics techniques for more effective workforce management Learn how people analytics benefits organizations of all sizes in various industries Integrate analytics into HR practices seamlessly and thoroughly Corporate executives need fact-based insights into what will happen with their talent. Who should you hire? Who should you promote? Who are the top or bottom performers, and why? Who is at risk to quit, and why? Analytics can provide these answers, and give you insights based on quantifiable data instead of gut feeling and subjective assessment. People Analytics in the Era of Big Data is the essential guide to optimizing your workforce with the tools already at your disposal.
Big Data Analytics
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Author : Ümit Demirbaga
language : en
Publisher: Springer Nature
Release Date : 2024-05-07
Big Data Analytics written by Ümit Demirbaga and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-07 with Computers categories.
This book introduces readers to big data analytics. It covers the background to and the concepts of big data, big data analytics, and cloud computing, along with the process of setting up, configuring, and getting familiar with the big data analytics working environments in the first two chapters. The third chapter provides comprehensive information on big data processing systems - from installing these systems to implementing real-world data applications, along with the necessary codes. The next chapter dives into the details of big data storage technologies, including their types, essentiality, durability, and availability, and reveals their differences in their properties. The fifth and sixth chapters guide the reader through understanding, configuring, and performing the monitoring and debugging of big data systems and present the available commercial and open-source tools for this purpose. Chapter seven gives information about a trending machine learning, Bayesian network: a probabilistic graphical model, by presenting a real-world probabilistic application to understand causal, complex, and hidden relationships for diagnosis and forecasting in a scalable manner for big data. Special sections throughout the eighth chapter present different case studies and applications to help the readers to develop their big data analytics skills using various big data analytics frameworks. The book will be of interest to business executives and IT managers as well as university students and their course leaders, in fact all those who want to get involved in the big data world.
Building Big Data And Analytics Solutions In The Cloud
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Author : Wei-Dong Zhu
language : en
Publisher: IBM Redbooks
Release Date : 2014-12-08
Building Big Data And Analytics Solutions In The Cloud written by Wei-Dong Zhu and has been published by IBM Redbooks this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-12-08 with Computers categories.
Big data is currently one of the most critical emerging technologies. Organizations around the world are looking to exploit the explosive growth of data to unlock previously hidden insights in the hope of creating new revenue streams, gaining operational efficiencies, and obtaining greater understanding of customer needs. It is important to think of big data and analytics together. Big data is the term used to describe the recent explosion of different types of data from disparate sources. Analytics is about examining data to derive interesting and relevant trends and patterns, which can be used to inform decisions, optimize processes, and even drive new business models. With today's deluge of data comes the problems of processing that data, obtaining the correct skills to manage and analyze that data, and establishing rules to govern the data's use and distribution. The big data technology stack is ever growing and sometimes confusing, even more so when we add the complexities of setting up big data environments with large up-front investments. Cloud computing seems to be a perfect vehicle for hosting big data workloads. However, working on big data in the cloud brings its own challenge of reconciling two contradictory design principles. Cloud computing is based on the concepts of consolidation and resource pooling, but big data systems (such as Hadoop) are built on the shared nothing principle, where each node is independent and self-sufficient. A solution architecture that can allow these mutually exclusive principles to coexist is required to truly exploit the elasticity and ease-of-use of cloud computing for big data environments. This IBM® RedpaperTM publication is aimed at chief architects, line-of-business executives, and CIOs to provide an understanding of the cloud-related challenges they face and give prescriptive guidance for how to realize the benefits of big data solutions quickly and cost-effectively.
Big Data Analytics
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Author : Mr. P. Ezhumalai
language : en
Publisher: Quill Tech Publications
Release Date : 2025-05-05
Big Data Analytics written by Mr. P. Ezhumalai and has been published by Quill Tech Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-05 with categories.
Big Data Analytics delves deep into the transformative world of data science, offering rich insights into how vast volumes of data are collected, processed, analyzed, and translated into actionable intelligence across industries. As the digital universe expands at a staggering rate—driven by IoT devices, social media, cloud computing, and enterprise systems—the need to extract meaningful patterns and trends from this deluge of information has never been greater. Our platform serves as a vital resource for data professionals, business leaders, researchers, and tech enthusiasts seeking to understand the technologies, methodologies, and real-world applications of big data. From foundational concepts like distributed computing, data warehousing, and parallel processing to advanced topics such as artificial intelligence, deep learning, real-time stream analytics, and predictive modeling, we offer content that is both accessible and technically rigorous. We spotlight major tools and frameworks like Hadoop, Spark, Kafka, Hive, and NoSQL databases, exploring how they are implemented in production environments. The publication also dives into data governance, quality, security, and ethical concerns, ensuring readers stay informed about responsible data practices. Through expert-authored articles, white papers, interviews with industry leaders, and in-depth case studies, we provide a 360-degree view of the data ecosystem. Each feature aims to bridge the gap between data theory and practice, illustrating how data-driven decisions improve business outcomes, customer engagement, and operational efficiency. From optimizing supply chains and forecasting market trends to detecting fraud and personalizing user experiences, big data is at the heart of innovation. Big Data Analytics covers applications across sectors like healthcare, finance, manufacturing, transportation, energy, education, and e-commerce, showing how data fuels smarter solutions in both public and private domains. Whether it's cloud-native data architectures, edge computing, or hybrid data environments, we explore the evolving infrastructure behind scalable analytics. Our audience includes not only experienced data scientists and engineers, but also business strategists, digital transformation officers, and students entering the field. We believe in democratizing data knowledge by making it comprehensive, current, and engaging. With the integration of machine learning and AI into every facet of modern analytics, the future of big data is more dynamic than ever, and our publication is here to chart that journey. As organizations strive for agility, resilience, and competitiveness in a data-first world, understanding how to harness big data becomes a strategic imperative. Big Data Analytics stands as your guide in this landscape—providing clarity, depth, and vision in a domain where information is power.
Big Data Analytics
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Author : Mrutyunjaya Panda
language : en
Publisher: CRC Press
Release Date : 2018-12-12
Big Data Analytics written by Mrutyunjaya Panda and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-12 with Business & Economics categories.
Social networking has increased drastically in recent years, resulting in an increased amount of data being created daily. Furthermore, diversity of issues and complexity of the social networks pose a challenge in social network mining. Traditional algorithm software cannot deal with such complex and vast amounts of data, necessitating the development of novel analytic approaches and tools. This reference work deals with social network aspects of big data analytics. It covers theory, practices and challenges in social networking. The book spans numerous disciplines like neural networking, deep learning, artificial intelligence, visualization, e-learning in higher education, e-healthcare, security and intrusion detection.
Big Data Analytics
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Author : Kiran Chaudhary
language : en
Publisher: CRC Press
Release Date : 2021-12-27
Big Data Analytics written by Kiran Chaudhary and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-12-27 with Business & Economics categories.
Big Data Analytics: Applications in Business and Marketing explores the concepts and applications related to marketing and business as well as future research directions. It also examines how this emerging field could be extended to performance management and decision-making. Investment in business and marketing analytics can create value through proper allocation of resources and resource orchestration process. The use of data analytics tools can be used to diagnose and improve performance. The book is divided into five parts. The first part introduces data science, big data, and data analytics. The second part focuses on applications of business analytics including: Big data analytics and algorithm Market basket analysis Anticipating consumer purchase behavior Variation in shopping patterns Big data analytics for market intelligence The third part looks at business intelligence and features an evaluation study of churn prediction models for business Intelligence. The fourth part of the book examines analytics for marketing decision-making and the roles of big data analytics for market intelligence and of consumer behavior. The book concludes with digital marketing, marketing by consumer analytics, web analytics for digital marketing, and smart retailing. This book covers the concepts, applications and research trends of marketing and business analytics with the aim of helping organizations increase profitability by improving decision-making through data analytics.