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Principles of Big Data

Principles of Big Data
Preparing, Sharing, and Analyzing Complex Information

by Jules J. Berman

  • Publisher : Newnes
  • Release : 2013-05-20
  • Pages : 288
  • ISBN : 0124047246
  • Language : En, Es, Fr & De
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Principles of Big Data helps readers avoid the common mistakes that endanger all Big Data projects. By stressing simple, fundamental concepts, this book teaches readers how to organize large volumes of complex data, and how to achieve data permanence when the content of the data is constantly changing. General methods for data verification and validation, as specifically applied to Big Data resources, are stressed throughout the book. The book demonstrates how adept analysts can find relationships among data objects held in disparate Big Data resources, when the data objects are endowed with semantic support (i.e., organized in classes of uniquely identified data objects). Readers will learn how their data can be integrated with data from other resources, and how the data extracted from Big Data resources can be used for purposes beyond those imagined by the data creators. Learn general methods for specifying Big Data in a way that is understandable to humans and to computers Avoid the pitfalls in Big Data design and analysis Understand how to create and use Big Data safely and responsibly with a set of laws, regulations and ethical standards that apply to the acquisition, distribution and integration of Big Data resources

Information Governance Principles and Practices for a Big Data Landscape

Information Governance Principles and Practices for a Big Data Landscape
A Book

by Chuck Ballard,Cindy Compert,Tom Jesionowski,Ivan Milman,Bill Plants,Barry Rosen,Harald Smith,IBM Redbooks

  • Publisher : IBM Redbooks
  • Release : 2014-03-31
  • Pages : 280
  • ISBN : 0738439592
  • Language : En, Es, Fr & De
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This IBM® Redbooks® publication describes how the IBM Big Data Platform provides the integrated capabilities that are required for the adoption of Information Governance in the big data landscape. As organizations embark on new use cases, such as Big Data Exploration, an enhanced 360 view of customers, or Data Warehouse modernization, and absorb ever growing volumes and variety of data with accelerating velocity, the principles and practices of Information Governance become ever more critical to ensure trust in data and help organizations overcome the inherent risks and achieve the wanted value. The introduction of big data changes the information landscape. Data arrives faster than humans can react to it, and issues can quickly escalate into significant events. The variety of data now poses new privacy and security risks. The high volume of information in all places makes it harder to find where these issues, risks, and even useful information to drive new value and revenue are. Information Governance provides an organization with a framework that can align their wanted outcomes with their strategic management principles, the people who can implement those principles, and the architecture and platform that are needed to support the big data use cases. The IBM Big Data Platform, coupled with a framework for Information Governance, provides an approach to build, manage, and gain significant value from the big data landscape.

Big Data

Big Data
Principles and Paradigms

by Rajkumar Buyya,Amir Vahid Dastjerdi,Rodrigo N Calheiros

  • Publisher : Morgan Kaufmann Publishers
  • Release : 2016-06-09
  • Pages : 494
  • ISBN : 9780128053942
  • Language : En, Es, Fr & De
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"Big Data: Principles and Paradigms" captures the state-of-the-art research on the architectural aspects, technologies, and applications of Big Data. The book identifies potential future directions and technologies that facilitate insight into numerous scientific, business, and consumer applications. To help realize Big Data s full potential, the book addresses numerous challenges, offering the conceptual and technological solutions for tackling them. These challenges include life-cycle data management, large-scale storage, flexible processing infrastructure, data modeling, scalable machine learning, data analysis algorithms, sampling techniques, and privacy and ethical issues. Covers computational platforms supporting Big Data applicationsAddresses key principles underlying Big Data computingExamines key developments supporting next generation Big Data platformsExplores the challenges in Big Data computing and ways to overcome themContains expert contributors from both academia and industry"

Principles and Practice of Big Data

Principles and Practice of Big Data
Preparing, Sharing, and Analyzing Complex Information

by Jules J Berman

  • Publisher : Academic Press
  • Release : 2018-07-23
  • Pages : 480
  • ISBN : 0128156104
  • Language : En, Es, Fr & De
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Principles and Practice of Big Data: Preparing, Sharing, and Analyzing Complex Information, Second Edition updates and expands on the first edition, bringing a set of techniques and algorithms that are tailored to Big Data projects. The book stresses the point that most data analyses conducted on large, complex data sets can be achieved without the use of specialized suites of software (e.g., Hadoop), and without expensive hardware (e.g., supercomputers). The core of every algorithm described in the book can be implemented in a few lines of code using just about any popular programming language (Python snippets are provided). Through the use of new multiple examples, this edition demonstrates that if we understand our data, and if we know how to ask the right questions, we can learn a great deal from large and complex data collections. The book will assist students and professionals from all scientific backgrounds who are interested in stepping outside the traditional boundaries of their chosen academic disciplines. Presents new methodologies that are widely applicable to just about any project involving large and complex datasets Offers readers informative new case studies across a range scientific and engineering disciplines Provides insights into semantics, identification, de-identification, vulnerabilities and regulatory/legal issues Utilizes a combination of pseudocode and very short snippets of Python code to show readers how they may develop their own projects without downloading or learning new software

Big Data Analytics

Big Data Analytics
Methods and Applications

by Saumyadipta Pyne,B.L.S. Prakasa Rao,S.B. Rao

  • Publisher : Springer
  • Release : 2016-10-12
  • Pages : 276
  • ISBN : 8132236289
  • Language : En, Es, Fr & De
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This book has a collection of articles written by Big Data experts to describe some of the cutting-edge methods and applications from their respective areas of interest, and provides the reader with a detailed overview of the field of Big Data Analytics as it is practiced today. The chapters cover technical aspects of key areas that generate and use Big Data such as management and finance; medicine and healthcare; genome, cytome and microbiome; graphs and networks; Internet of Things; Big Data standards; bench-marking of systems; and others. In addition to different applications, key algorithmic approaches such as graph partitioning, clustering and finite mixture modelling of high-dimensional data are also covered. The varied collection of themes in this volume introduces the reader to the richness of the emerging field of Big Data Analytics.

Principles of Risk Analysis

Principles of Risk Analysis
Decision Making Under Uncertainty

by Charles Yoe

  • Publisher : CRC Press
  • Release : 2019-01-30
  • Pages : 816
  • ISBN : 0429667612
  • Language : En, Es, Fr & De
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In every decision problem there are things we know and things we do not know. Risk analysis science uses the best available evidence to assess what we know while it is carefully intentional in the way it addresses the importance of the things we do not know in the evaluation of decision choices and decision outcomes. The field of risk analysis science continues to expand and grow and the second edition of Principles of Risk Analysis: Decision Making Under Uncertainty responds to this evolution with several significant changes. The language has been updated and expanded throughout the text and the book features several new areas of expansion including five new chapters. The book’s simple and straightforward style—based on the author’s decades of experience as a risk analyst, trainer, and educator—strips away the mysterious aura that often accompanies risk analysis. Features: Details the tasks of risk management, risk assessment, and risk communication in a straightforward, conceptual manner Provides sufficient detail to empower professionals in any discipline to become risk practitioners Expands the risk management emphasis with a new chapter to serve private industry and a growing public sector interest in the growing practice of enterprise risk management Describes dozens of quantitative and qualitative risk assessment tools in a new chapter Practical guidance and ideas for using risk science to improve decisions and their outcomes is found in a new chapter on decision making under uncertainty Practical methods for helping risk professionals to tell their risk story are the focus of a new chapter Features an expanded set of examples of the risk process that demonstrate the growing applications of risk analysis As before, this book continues to appeal to professionals who want to learn and apply risk science in their own professions as well as students preparing for professional careers. This book remains a discipline free guide to the principles of risk analysis that is accessible to all interested practitioners. Files used in the creation of this book and additional exercises as well as a free student version of Palisade Corporation’s Decision Tools Suite software are available with the purchase of this book. A less detailed introduction to the risk analysis science tasks of risk management, risk assessment, and risk communication is found in Primer of Risk Analysis: Decision Making Under Uncertainty, Second Edition, ISBN: 978-1-138-31228-9.

Management in the Era of Big Data

Management in the Era of Big Data
Issues and Challenges

by Joanna Paliszkiewicz

  • Publisher : CRC Press
  • Release : 2020-06-15
  • Pages : 222
  • ISBN : 1000093670
  • Language : En, Es, Fr & De
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This book is a wonderful collection of chapters that posits how managers need to cope in the Big Data era. It highlights many of the emerging developments in technologies, applications, and trends related to management’s needs in this Big Data era. —Dr. Jay Liebowitz, Harrisburg University of Science and Technology This book presents some meaningful work on Big Data analytics and its applications. Each chapter generates helpful guidance to the readers on Big Data analytics and its applications, challenges, and prospects that is necessary for organizational strategic direction. —Dr. Alex Koohang, Middle Georgia State University Big Data is a concept that has caught the attention of practitioners, academicians, and researchers. Big Data offers organizations the possibility of gaining a competitive advantage by managing, collecting, and analyzing massive amounts of data. As the promises and challenges posed by Big Data have increased over the past decade, significant issues have developed regarding how data can be used for improving management. Big Data can be understood as large amounts of data generated by the Internet and a variety of connected smart devices and sensors. This book discusses the main challenges posed by Big Data in a manner relevant to both practitioners and scholars. It examines how companies can leverage Big Data analytics to act and optimize the business. This book brings together the theory and practice of management in the era of Big Data. It offers a look at the current state of Big Data, including a comprehensive overview of both research and practical applications. By bringing together conceptual thinking and empirical research on the nature, meaning, and development of Big Data in management, this book unifies research on Big Data in management to stimulate new directions for academic investigation as well as practice.

Research Anthology on Big Data Analytics, Architectures, and Applications

Research Anthology on Big Data Analytics, Architectures, and Applications
A Book

by Management Association, Information Resources

  • Publisher : IGI Global
  • Release : 2021-09-24
  • Pages : 1988
  • ISBN : 1668436639
  • Language : En, Es, Fr & De
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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.

Principles of Big Data

Principles of Big Data
Preparing, Sharing, and Analyzing Complex Information

by Jules J. Berman

  • Publisher : Newnes
  • Release : 2013-05-20
  • Pages : 288
  • ISBN : 9780124047242
  • Language : En, Es, Fr & De
GET BOOK

Principles of Big Data helps readers avoid the common mistakes that endanger all Big Data projects. By stressing simple, fundamental concepts, this book teaches readers how to organize large volumes of complex data, and how to achieve data permanence when the content of the data is constantly changing. General methods for data verification and validation, as specifically applied to Big Data resources, are stressed throughout the book. The book demonstrates how adept analysts can find relationships among data objects held in disparate Big Data resources, when the data objects are endowed with semantic support (i.e., organized in classes of uniquely identified data objects). Readers will learn how their data can be integrated with data from other resources, and how the data extracted from Big Data resources can be used for purposes beyond those imagined by the data creators. • Learn general methods for specifying Big Data in a way that is understandable to humans and to computers. • Avoid the pitfalls in Big Data design and analysis. • Understand how to create and use Big Data safely and responsibly with a set of laws, regulations and ethical standards that apply to the acquisition, distribution and integration of Big Data resources.

Big Data Management

Big Data Management
Data Governance Principles for Big Data Analytics

by Peter Ghavami

  • Publisher : Walter de Gruyter GmbH & Co KG
  • Release : 2020-11-09
  • Pages : 174
  • ISBN : 3110664062
  • Language : En, Es, Fr & De
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Data analytics is core to business and decision making. The rapid increase in data volume, velocity and variety offers both opportunities and challenges. While open source solutions to store big data, like Hadoop, offer platforms for exploring value and insight from big data, they were not originally developed with data security and governance in mind. Big Data Management discusses numerous policies, strategies and recipes for managing big data. It addresses data security, privacy, controls and life cycle management offering modern principles and open source architectures for successful governance of big data. The author has collected best practices from the world’s leading organizations that have successfully implemented big data platforms. The topics discussed cover the entire data management life cycle, data quality, data stewardship, regulatory considerations, data council, architectural and operational models are presented for successful management of big data. The book is a must-read for data scientists, data engineers and corporate leaders who are implementing big data platforms in their organizations.

Big Data in Context

Big Data in Context
Legal, Social and Technological Insights

by Thomas Hoeren,Barbara Kolany-Raiser

  • Publisher : Springer
  • Release : 2017-10-17
  • Pages : 120
  • ISBN : 331962461X
  • Language : En, Es, Fr & De
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This book is open access under a CC BY 4.0 license. This book sheds new light on a selection of big data scenarios from an interdisciplinary perspective. It features legal, sociological and economic approaches to fundamental big data topics such as privacy, data quality and the ECJ’s Safe Harbor decision on the one hand, and practical applications such as smart cars, wearables and web tracking on the other. Addressing the interests of researchers and practitioners alike, it provides a comprehensive overview of and introduction to the emerging challenges regarding big data.All contributions are based on papers submitted in connection with ABIDA (Assessing Big Data), an interdisciplinary research project exploring the societal aspects of big data and funded by the German Federal Ministry of Education and Research.This volume was produced as a part of the ABIDA project (Assessing Big Data, 01IS15016A-F). ABIDA is a four-year collaborative project funded by the Federal Ministry of Education and Research. However the views and opinions expressed in this book reflect only the authors’ point of view and not necessarily those of all members of the ABIDA project or the Federal Ministry of Education and Research.

Harness Oil and Gas Big Data with Analytics

Harness Oil and Gas Big Data with Analytics
Optimize Exploration and Production with Data-Driven Models

by Keith R. Holdaway

  • Publisher : John Wiley & Sons
  • Release : 2014-05-27
  • Pages : 384
  • ISBN : 1118779312
  • Language : En, Es, Fr & De
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Use big data analytics to efficiently drive oil and gas exploration and production Harness Oil and Gas Big Data with Analytics provides a complete view of big data and analytics techniques as they are applied to the oil and gas industry. Including a compendium of specific case studies, the book underscores the acute need for optimization in the oil and gas exploration and production stages and shows how data analytics can provide such optimization. This spans exploration, development, production and rejuvenation of oil and gas assets. The book serves as a guide for fully leveraging data, statistical, and quantitative analysis, exploratory and predictive modeling, and fact-based management to drive decision making in oil and gas operations. This comprehensive resource delves into the three major issues that face the oil and gas industry during the exploration and production stages: Data management, including storing massive quantities of data in a manner conducive to analysis and effectively retrieving, backing up, and purging data Quantification of uncertainty, including a look at the statistical and data analytics methods for making predictions and determining the certainty of those predictions Risk assessment, including predictive analysis of the likelihood that known risks are realized and how to properly deal with unknown risks Covering the major issues facing the oil and gas industry in the exploration and production stages, Harness Big Data with Analytics reveals how to model big data to realize efficiencies and business benefits.

Privacy and Power

Privacy and Power
A Transatlantic Dialogue in the Shadow of the NSA-Affair

by Russell A. Miller

  • Publisher : Cambridge University Press
  • Release : 2017-02-23
  • Pages : 805
  • ISBN : 1107154049
  • Language : En, Es, Fr & De
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This book documents and explains the differences in the ways Americans and Europeans approach the issues of privacy and intelligence gathering.

Data Science and Big Data Analytics

Data Science and Big Data Analytics
ACM-WIR 2018

by Durgesh Kumar Mishra,Xin-She Yang,Aynur Unal

  • Publisher : Springer
  • Release : 2018-08-01
  • Pages : 406
  • ISBN : 9811076413
  • Language : En, Es, Fr & De
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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.

Process Safety and Big Data

Process Safety and Big Data
A Book

by Sagit Valeev,Natalya Kondratyeva

  • Publisher : Elsevier
  • Release : 2021-02-18
  • Pages : 312
  • ISBN : 0128220678
  • Language : En, Es, Fr & De
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Process Safety and Big Data discusses the principles of process safety and advanced information technologies. It explains how these principles are applied to the process industry and provides examples of applications in process safety control and decision support systems. This book helps to address problems that researchers face in industry that are the result of increased process complexity and that have an impact on safety issues. It shows ways to tackle these safety issues by implementing modern information technologies, such as big data analysis and artificial intelligence. It provides an integrated approach to modern information technologies used in control and management of process safety in industry. The book also considers indicators and criteria in effective safety decisions, and addresses the issue of how big data would provide support for improved, autonomous, data-driven decisions. Paves the way for the digital transformation of safety science and safety management Takes a system approach to advanced information technologies used in process safety Applies big data technologies to process safety Includes multiple pertinent case studies

Taxonomic Guide to Infectious Diseases

Taxonomic Guide to Infectious Diseases
Understanding the Biologic Classes of Pathogenic Organisms

by Jules J. Berman

  • Publisher : Academic Press
  • Release : 2019-05-31
  • Pages : 399
  • ISBN : 012817577X
  • Language : En, Es, Fr & De
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Taxonomic Guide to Infectious Diseases: Understanding the Biologic Classes of Pathogenic Organisms, Second Edition tackles the complexity of clinical microbiology by assigning every infectious organism to one of 40+ taxonomic classes and providing a description of the defining traits that apply to all the organisms within each class. This edition is an updated, revised and greatly expanded guide to the classes of organisms that infect humans. This book will provide students and clinicians alike with a simplified way to understand the complex fields of clinical microbiology and parasitology. Focuses on human disease processes and includes numerous clinical tips for healthcare providers Describes the principles of classification and explains why the science of taxonomy is vital to the fields of bioinformatics and modern disease research Provides images of prototypical organisms for taxonomic classes Includes a section that lists common taxonomic pitfalls and how they can be avoided

Data-Driven Innovation Big Data for Growth and Well-Being

Data-Driven Innovation Big Data for Growth and Well-Being
Big Data for Growth and Well-Being

by OECD

  • Publisher : OECD Publishing
  • Release : 2015-10-06
  • Pages : 456
  • ISBN : 9264229353
  • Language : En, Es, Fr & De
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This report improves the evidence base on the role of Data Driven Innovation for promoting growth and well-being, and provide policy guidance on how to maximise the benefits of DDI and mitigate the associated economic and societal risks.

Emerging Technologies in Data Mining and Information Security

Emerging Technologies in Data Mining and Information Security
Proceedings of IEMIS 2018, Volume 2

by Ajith Abraham,Paramartha Dutta,Jyotsna Kumar Mandal,Abhishek Bhattacharya,Soumi Dutta

  • Publisher : Springer
  • Release : 2018-09-01
  • Pages : 885
  • ISBN : 9811314985
  • Language : En, Es, Fr & De
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The book features research papers presented at the International Conference on Emerging Technologies in Data Mining and Information Security (IEMIS 2018) held at the University of Engineering & Management, Kolkata, India, on February 23–25, 2018. It comprises high-quality research by academics and industrial experts in the field of computing and communication, including full-length papers, research-in-progress papers, case studies related to all the areas of data mining, machine learning, IoT and information security.

Trends in Telecommunication Reform 2015

Trends in Telecommunication Reform 2015
A Book

by International Telecommunication Union

  • Publisher : United Nations
  • Release : 2017-07-11
  • Pages : 240
  • ISBN : 9261179614
  • Language : En, Es, Fr & De
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Under the overarching theme "Getting ready for the digital economy", the 15th edition of Trends in Telecommunication Reform discusses changing ICT consumer behaviour, consumer empowerment and protection in the digital age. It further explores the opportunities and challenges of big data and what it means from a regulatory perspective; why competition matters. It also attempts to answer whether it is time to rethink spectrum licensing, how to monitor the implementation of broadband plans and what are the new business models driven by digital communications and services. As in previous editions, the publication will feature an in-depth analysis of current market and regulatory trends based on ITU data from one of the world's most comprehensive data platforms, the ICT Eye.

Big Data in Small Business

Big Data in Small Business
Data-Driven Growth in Small and Medium-Sized Enterprises

by Lund Pedersen, Carsten,Lindgreen, Adam,Ritter, Thomas,Ringberg, Torsten

  • Publisher : Edward Elgar Publishing
  • Release : 2021-09-21
  • Pages : 272
  • ISBN : 1839100168
  • Language : En, Es, Fr & De
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This important book considers the ways in which small and medium-sized enterprises (SMEs) can thrive in the age of big data. To address this central issue from multiple viewpoints, the editors introduce a collection of experiences, insights, and guidelines from a variety of expert researchers, each of whom provides a piece to solve this puzzle.