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Principles of Big Data

Principles of Big Data
  • Author : Jules J. Berman
  • Publsiher : Newnes
  • Release : 20 May 2013
  • ISBN : 0124047246
  • Pages : 288 pages
  • Rating : 4/5 from 21 ratings
GET THIS BOOKPrinciples of Big Data

Summary:
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


Principles of Big Data

Principles of Big Data
  • Author : Jules J. Berman
  • Publisher : Newnes
  • Release : 20 May 2013
GET THIS BOOKPrinciples of Big Data

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


Big Data

Big Data
  • Author : Rajkumar Buyya,Rodrigo N. Calheiros,Amir Vahid Dastjerdi
  • Publisher : Morgan Kaufmann
  • Release : 07 June 2016
GET THIS BOOKBig Data

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,


Big Data Management

Big Data Management
  • Author : Peter Ghavami
  • Publisher : Walter de Gruyter GmbH & Co KG
  • Release : 09 November 2020
GET THIS BOOKBig Data Management

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


Big Data

Big Data
  • Author : Nathan Marz,James Warren
  • Publisher : Manning Publications Company
  • Release : 06 March 2021
GET THIS BOOKBig Data

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


Applied Data Analytics - Principles and Applications

Applied Data Analytics - Principles and Applications
  • Author : Johnson I. Agbinya
  • Publisher : River Publishers Signal, Image
  • Release : 30 July 2019
GET THIS BOOKApplied Data Analytics - Principles and Applications

The emergence of huge amounts of data which require analysis and in some cases real-time processing has forced exploration into fast algorithms for handling very large data sizes. Analysis of x-ray images in medical applications, cyber security data, crime data, telecommunications and stock market data, health records and business analytics data are but a few areas of interest. Applications and platforms including R, RapidMiner and Weka provide the basis for analysis, often used by practitioners who pay little to no


Big Data Analytics in U.S. Courts

Big Data Analytics in U.S. Courts
  • Author : Dwight Steward,Roberto Cavazos
  • Publisher : Springer Nature
  • Release : 14 November 2019
GET THIS BOOKBig Data Analytics in U.S. Courts

This Palgrave Pivot identifies the key legal, economic, and policy issues surrounding the allowance to use and interpret electronic data consistently and in a scientifically valid manner in U.S. courts. Evidence based on the analysis of large amounts of electronic data ("Big Data") plays an increasing role in civil court disputes, providing information that could not have been obtained from a witness stand. While Big Data evidence presents opportunities, it also presents legal and public policy challenges and concerns.


Information Governance Principles and Practices for a Big Data Landscape

Information Governance Principles and Practices for a Big Data Landscape
  • Author : Chuck Ballard,Cindy Compert,Tom Jesionowski,Ivan Milman,Bill Plants,Barry Rosen,Harald Smith,IBM Redbooks
  • Publisher : IBM Redbooks
  • Release : 31 March 2014
GET THIS BOOKInformation Governance Principles and Practices for a Big Data Landscape

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


The Politics and Policies of Big Data

The Politics and Policies of Big Data
  • Author : Ann Rudinow Sætnan,Ingrid Schneider,Nicola Green
  • Publisher : Routledge
  • Release : 08 May 2018
GET THIS BOOKThe Politics and Policies of Big Data

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



Principles of Data Science

Principles of Data Science
  • Author : Sinan Ozdemir
  • Publisher : Packt Publishing Ltd
  • Release : 16 December 2016
GET THIS BOOKPrinciples of Data Science

Learn the techniques and math you need to start making sense of your data About This Book Enhance your knowledge of coding with data science theory for practical insight into data science and analysis More than just a math class, learn how to perform real-world data science tasks with R and Python Create actionable insights and transform raw data into tangible value Who This Book Is For You should be fairly well acquainted with basic algebra and should feel comfortable


Big Data Analysis: New Algorithms for a New Society

Big Data Analysis: New Algorithms for a New Society
  • Author : Nathalie Japkowicz,Jerzy Stefanowski
  • Publisher : Springer
  • Release : 16 December 2015
GET THIS BOOKBig Data Analysis: New Algorithms for a New Society

This edited volume is devoted to Big Data Analysis from a Machine Learning standpoint as presented by some of the most eminent researchers in this area. It demonstrates that Big Data Analysis opens up new research problems which were either never considered before, or were only considered within a limited range. In addition to providing methodological discussions on the principles of mining Big Data and the difference between traditional statistical data analysis and newer computing frameworks, this book presents recently


Principles of Managerial Statistics and Data Science

Principles of Managerial Statistics and Data Science
  • Author : Roberto Rivera
  • Publisher : John Wiley & Sons
  • Release : 19 February 2020
GET THIS BOOKPrinciples of Managerial Statistics and Data Science

Introduces readers to the principles of managerial statistics and data science, with an emphasis on statistical literacy of business students Through a statistical perspective, this book introduces readers to the topic of data science, including Big Data, data analytics, and data wrangling. Chapters include multiple examples showing the application of the theoretical aspects presented. It features practice problems designed to ensure that readers understand the concepts and can apply them using real data. Over 100 open data sets used for examples


Principles of Distributed Database Systems

Principles of Distributed Database Systems
  • Author : M. Tamer Özsu,Patrick Valduriez
  • Publisher : Springer Science & Business Media
  • Release : 24 February 2011
GET THIS BOOKPrinciples of Distributed Database Systems

This third edition of a classic textbook can be used to teach at the senior undergraduate and graduate levels. The material concentrates on fundamental theories as well as techniques and algorithms. The advent of the Internet and the World Wide Web, and, more recently, the emergence of cloud computing and streaming data applications, has forced a renewal of interest in distributed and parallel data management, while, at the same time, requiring a rethinking of some of the traditional techniques. This


Principles and Methods for Data Science

Principles and Methods for Data Science
  • Author : Anonim
  • Publisher : Elsevier
  • Release : 28 May 2020
GET THIS BOOKPrinciples and Methods for Data Science

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 Warehousing in the Age of Big Data

Data Warehousing in the Age of Big Data
  • Author : Krish Krishnan
  • Publisher : Newnes
  • Release : 02 May 2013
GET THIS BOOKData Warehousing in the Age of Big Data

Data Warehousing in the Age of the Big Data will help you and your organization make the most of unstructured data with your existing data warehouse. As Big Data continues to revolutionize how we use data, it doesn't have to create more confusion. Expert author Krish Krishnan helps you make sense of how Big Data fits into the world of data warehousing in clear and concise detail. The book is presented in three distinct parts. Part 1 discusses Big Data, its