Principles And Practice Of Big Data

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Principles of Big Data

Jules J. Berman
Principles of Big Data Book PDF

Author : Jules J. Berman
Publisher : Newnes
Page : 288 pages
File Size : 45,6 Mb
Release : 2013-05-20
Category : Computers
ISBN : 9780124047242

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Principles of Big Data by Jules J. Berman Pdf

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

James Warren,Nathan Marz
Big Data Book PDF

Author : James Warren,Nathan Marz
Publisher : Simon and Schuster
Page : 481 pages
File Size : 44,9 Mb
Release : 2015-04-29
Category : Computers
ISBN : 9781638351108

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Big Data by James Warren,Nathan Marz Pdf

Summary Big Data teaches you to build big data systems using an architecture that takes advantage of clustered hardware along with new tools designed specifically to capture and analyze web-scale data. It describes a scalable, easy-to-understand approach to big data systems that can be built and run by a small team. Following a realistic example, this book guides readers through the theory of big data systems, how to implement them in practice, and how to deploy and operate them once they're built. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Book Web-scale applications like social networks, real-time analytics, or e-commerce sites deal with a lot of data, whose volume and velocity exceed the limits of traditional database systems. These applications require architectures built around clusters of machines to store and process data of any size, or speed. Fortunately, scale and simplicity are not mutually exclusive. Big Data teaches you to build big data systems using an architecture designed specifically to capture and analyze web-scale data. This book presents the Lambda Architecture, a scalable, easy-to-understand approach that can be built and run by a small team. You'll explore the theory of big data systems and how to implement them in practice. In addition to discovering a general framework for processing big data, you'll learn specific technologies like Hadoop, Storm, and NoSQL databases. This book requires no previous exposure to large-scale data analysis or NoSQL tools. Familiarity with traditional databases is helpful. What's Inside Introduction to big data systems Real-time processing of web-scale data Tools like Hadoop, Cassandra, and Storm Extensions to traditional database skills About the Authors Nathan Marz is the creator of Apache Storm and the originator of the Lambda Architecture for big data systems. James Warren is an analytics architect with a background in machine learning and scientific computing. Table of Contents A new paradigm for Big Data PART 1 BATCH LAYER Data model for Big Data Data model for Big Data: Illustration Data storage on the batch layer Data storage on the batch layer: Illustration Batch layer Batch layer: Illustration An example batch layer: Architecture and algorithms An example batch layer: Implementation PART 2 SERVING LAYER Serving layer Serving layer: Illustration PART 3 SPEED LAYER Realtime views Realtime views: Illustration Queuing and stream processing Queuing and stream processing: Illustration Micro-batch stream processing Micro-batch stream processing: Illustration Lambda Architecture in depth

Big Data Management

Peter Ghavami
Big Data Management Book PDF

Author : Peter Ghavami
Publisher : Walter de Gruyter GmbH & Co KG
Page : 180 pages
File Size : 44,5 Mb
Release : 2020-11-09
Category : Business & Economics
ISBN : 9783110664324

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Big Data Management by Peter Ghavami Pdf

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

Rajkumar Buyya,Rodrigo N. Calheiros,Amir Vahid Dastjerdi
Big Data Book PDF

Author : Rajkumar Buyya,Rodrigo N. Calheiros,Amir Vahid Dastjerdi
Publisher : Morgan Kaufmann
Page : 494 pages
File Size : 54,7 Mb
Release : 2016-06-07
Category : Computers
ISBN : 9780128093467

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Big Data by Rajkumar Buyya,Rodrigo N. Calheiros,Amir Vahid Dastjerdi Pdf

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 applications Addresses key principles underlying Big Data computing Examines key developments supporting next generation Big Data platforms Explores the challenges in Big Data computing and ways to overcome them Contains expert contributors from both academia and industry

Data Privacy

Nataraj Venkataramanan,Ashwin Shriram
Data Privacy Book PDF

Author : Nataraj Venkataramanan,Ashwin Shriram
Publisher : CRC Press
Page : 296 pages
File Size : 52,6 Mb
Release : 2016-10-03
Category : Computers
ISBN : 9781315353760

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Data Privacy by Nataraj Venkataramanan,Ashwin Shriram Pdf

The book covers data privacy in depth with respect to data mining, test data management, synthetic data generation etc. It formalizes principles of data privacy that are essential for good anonymization design based on the data format and discipline. The principles outline best practices and reflect on the conflicting relationship between privacy and utility. From a practice standpoint, it provides practitioners and researchers with a definitive guide to approach anonymization of various data formats, including multidimensional, longitudinal, time-series, transaction, and graph data. In addition to helping CIOs protect confidential data, it also offers a guideline as to how this can be implemented for a wide range of data at the enterprise level.

Principles of Database Management

Wilfried Lemahieu,Seppe vanden Broucke,Bart Baesens
Principles of Database Management Book PDF

Author : Wilfried Lemahieu,Seppe vanden Broucke,Bart Baesens
Publisher : Cambridge University Press
Page : 817 pages
File Size : 47,7 Mb
Release : 2018-07-12
Category : Computers
ISBN : 9781107186125

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Principles of Database Management by Wilfried Lemahieu,Seppe vanden Broucke,Bart Baesens Pdf

Introductory, theory-practice balanced text teaching the fundamentals of databases to advanced undergraduates or graduate students in information systems or computer science.

Principles and Practice of Big Data

Jules J Berman
Principles and Practice of Big Data Book PDF

Author : Jules J Berman
Publisher : Academic Press
Page : 480 pages
File Size : 45,8 Mb
Release : 2018-07-23
Category : Computers
ISBN : 9780128156100

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Principles and Practice of Big Data by Jules J Berman Pdf

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

The Politics and Policies of Big Data

Ann Rudinow Sætnan,Ingrid Schneider,Nicola Green
The Politics and Policies of Big Data Book PDF

Author : Ann Rudinow Sætnan,Ingrid Schneider,Nicola Green
Publisher : Routledge
Page : 358 pages
File Size : 50,5 Mb
Release : 2018-05-08
Category : Social Science
ISBN : 9781351866545

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The Politics and Policies of Big Data by Ann Rudinow Sætnan,Ingrid Schneider,Nicola Green Pdf

Big Data, gathered together and re-analysed, can be used to form endless variations of our persons - so-called ‘data doubles’. Whilst never a precise portrayal of who we are, they unarguably contain glimpses of details about us that, when deployed into various routines (such as management, policing and advertising) can affect us in many ways. How are we to deal with Big Data? When is it beneficial to us? When is it harmful? How might we regulate it? Offering careful and critical analyses, this timely volume aims to broaden well-informed, unprejudiced discourse, focusing on: the tenets of Big Data, the politics of governance and regulation; and Big Data practices, performance and resistance. An interdisciplinary volume, The Politics of Big Data will appeal to undergraduate and postgraduate students, as well as postdoctoral and senior researchers interested in fields such as Technology, Politics and Surveillance.

Big Data Imperatives

Soumendra Mohanty,Madhu Jagadeesh,Harsha Srivatsa
Big Data Imperatives Book PDF

Author : Soumendra Mohanty,Madhu Jagadeesh,Harsha Srivatsa
Publisher : Apress
Page : 311 pages
File Size : 44,7 Mb
Release : 2013-08-23
Category : Computers
ISBN : 9781430248736

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Big Data Imperatives by Soumendra Mohanty,Madhu Jagadeesh,Harsha Srivatsa Pdf

Big Data Imperatives, focuses on resolving the key questions on everyone’s mind: Which data matters? Do you have enough data volume to justify the usage? How you want to process this amount of data? How long do you really need to keep it active for your analysis, marketing, and BI applications? Big data is emerging from the realm of one-off projects to mainstream business adoption; however, the real value of big data is not in the overwhelming size of it, but more in its effective use. This book addresses the following big data characteristics: Very large, distributed aggregations of loosely structured data – often incomplete and inaccessible Petabytes/Exabytes of data Millions/billions of people providing/contributing to the context behind the data Flat schema's with few complex interrelationships Involves time-stamped events Made up of incomplete data Includes connections between data elements that must be probabilistically inferred Big Data Imperatives explains 'what big data can do'. It can batch process millions and billions of records both unstructured and structured much faster and cheaper. Big data analytics provide a platform to merge all analysis which enables data analysis to be more accurate, well-rounded, reliable and focused on a specific business capability. Big Data Imperatives describes the complementary nature of traditional data warehouses and big-data analytics platforms and how they feed each other. This book aims to bring the big data and analytics realms together with a greater focus on architectures that leverage the scale and power of big data and the ability to integrate and apply analytics principles to data which earlier was not accessible. This book can also be used as a handbook for practitioners; helping them on methodology,technical architecture, analytics techniques and best practices. At the same time, this book intends to hold the interest of those new to big data and analytics by giving them a deep insight into the realm of big data.

Big Data Analytics

Kim H. Pries,Robert Dunnigan
Big Data Analytics Book PDF

Author : Kim H. Pries,Robert Dunnigan
Publisher : CRC Press
Page : 576 pages
File Size : 41,7 Mb
Release : 2015-02-05
Category : Computers
ISBN : 9781482234527

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Big Data Analytics by Kim H. Pries,Robert Dunnigan Pdf

With this book, managers and decision makers are given the tools to make more informed decisions about big data purchasing initiatives. Big Data Analytics: A Practical Guide for Managers not only supplies descriptions of common tools, but also surveys the various products and vendors that supply the big data market.Comparing and contrasting the dif

Data Science and Big Data Analytics

EMC Education Services
Data Science and Big Data Analytics Book PDF

Author : EMC Education Services
Publisher : John Wiley & Sons
Page : 432 pages
File Size : 48,6 Mb
Release : 2015-01-05
Category : Computers
ISBN : 9781118876053

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Data Science and Big Data Analytics by EMC Education Services Pdf

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!

Information Governance Principles and Practices for a Big Data Landscape

Chuck Ballard,Cindy Compert,Tom Jesionowski,Ivan Milman,Bill Plants,Barry Rosen,Harald Smith,IBM Redbooks
Information Governance Principles and Practices for a Big Data Landscape Book PDF

Author : Chuck Ballard,Cindy Compert,Tom Jesionowski,Ivan Milman,Bill Plants,Barry Rosen,Harald Smith,IBM Redbooks
Publisher : IBM Redbooks
Page : 280 pages
File Size : 51,8 Mb
Release : 2014-03-31
Category : Computers
ISBN : 9780738439594

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Information Governance Principles and Practices for a Big Data Landscape by Chuck Ballard,Cindy Compert,Tom Jesionowski,Ivan Milman,Bill Plants,Barry Rosen,Harald Smith,IBM Redbooks Pdf

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 and Social Science

Ian Foster,Rayid Ghani,Ron S. Jarmin,Frauke Kreuter,Julia Lane
Big Data and Social Science Book PDF

Author : Ian Foster,Rayid Ghani,Ron S. Jarmin,Frauke Kreuter,Julia Lane
Publisher : CRC Press
Page : 320 pages
File Size : 51,8 Mb
Release : 2020-11-17
Category : Mathematics
ISBN : 9781000208634

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Big Data and Social Science by Ian Foster,Rayid Ghani,Ron S. Jarmin,Frauke Kreuter,Julia Lane Pdf

Big Data and Social Science: Data Science Methods and Tools for Research and Practice, Second Edition shows how to apply data science to real-world problems, covering all stages of a data-intensive social science or policy project. Prominent leaders in the social sciences, statistics, and computer science as well as the field of data science provide a unique perspective on how to apply modern social science research principles and current analytical and computational tools. The text teaches you how to identify and collect appropriate data, apply data science methods and tools to the data, and recognize and respond to data errors, biases, and limitations. Features: Takes an accessible, hands-on approach to handling new types of data in the social sciences Presents the key data science tools in a non-intimidating way to both social and data scientists while keeping the focus on research questions and purposes Illustrates social science and data science principles through real-world problems Links computer science concepts to practical social science research Promotes good scientific practice Provides freely available workbooks with data, code, and practical programming exercises, through Binder and GitHub New to the Second Edition: Increased use of examples from different areas of social sciences New chapter on dealing with Bias and Fairness in Machine Learning models Expanded chapters focusing on Machine Learning and Text Analysis Revamped hands-on Jupyter notebooks to reinforce concepts covered in each chapter This classroom-tested book fills a major gap in graduate- and professional-level data science and social science education. It can be used to train a new generation of social data scientists to tackle real-world problems and improve the skills and competencies of applied social scientists and public policy practitioners. It empowers you to use the massive and rapidly growing amounts of available data to interpret economic and social activities in a scientific and rigorous manner.

Principles and Methods for Data Science

Anonim
Principles and Methods for Data Science Book PDF

Author : Anonim
Publisher : Elsevier
Page : 498 pages
File Size : 51,7 Mb
Release : 2020-05-28
Category : Mathematics
ISBN : 9780444642127

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Principles and Methods for Data Science by Anonim Pdf

Principles and Methods for Data Science, Volume 43 in the Handbook of Statistics series, highlights new advances in the field, with this updated volume presenting interesting and timely topics, including Competing risks, aims and methods, Data analysis and mining of microbial community dynamics, Support Vector Machines, a robust prediction method with applications in bioinformatics, Bayesian Model Selection for Data with High Dimension, High dimensional statistical inference: theoretical development to data analytics, Big data challenges in genomics, Analysis of microarray gene expression data using information theory and stochastic algorithm, Hybrid Models, Markov Chain Monte Carlo Methods: Theory and Practice, and more. Provides the authority and expertise of leading contributors from an international board of authors Presents the latest release in the Handbook of Statistics series Updated release includes the latest information on Principles and Methods for Data Science

The Big Data Agenda

Annika Richterich
The Big Data Agenda Book PDF

Author : Annika Richterich
Publisher : University of Westminster Press
Page : 156 pages
File Size : 55,7 Mb
Release : 2018-04-13
Category : Social Science
ISBN : 9781911534730

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The Big Data Agenda by Annika Richterich Pdf

This book highlights that the capacity for gathering, analysing, and utilising vast amounts of digital (user) data raises significant ethical issues. Annika Richterich provides a systematic contemporary overview of the field of critical data studies that reflects on practices of digital data collection and analysis. The book assesses in detail one big data research area: biomedical studies, focused on epidemiological surveillance. Specific case studies explore how big data have been used in academic work. The Big Data Agenda concludes that the use of big data in research urgently needs to be considered from the vantage point of ethics and social justice. Drawing upon discourse ethics and critical data studies, Richterich argues that entanglements between big data research and technology/ internet corporations have emerged. In consequence, more opportunities for discussing and negotiating emerging research practices and their implications for societal values are needed.