Principles 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 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

Produk Detail:

  • Author : Jules J. Berman
  • Publisher : Newnes
  • Pages : 288 pages
  • ISBN : 0124047246
  • Rating : 4/5 from 21 reviews
CLICK HERE TO GET THIS BOOKPrinciples of Big Data

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 : Nathan Marz,James Warren
  • Publisher : Manning Publications Company
  • Release : 07 May 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

Principles and Practice of Big Data

Principles and Practice of Big Data
  • Author : Jules J Berman
  • Publisher : Academic Press
  • Release : 23 July 2018
GET THIS BOOKPrinciples and Practice of Big Data

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

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,

Principles and Practice of Big Data, 2nd Edition

Principles and Practice of Big Data, 2nd Edition
  • Author : Jules Berman
  • Publisher : Unknown Publisher
  • Release : 07 May 2021
GET THIS BOOKPrinciples and Practice of Big Data, 2nd Edition

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

Data Privacy

Data Privacy
  • Author : Nataraj Venkataramanan,Ashwin Shriram
  • Publisher : CRC Press
  • Release : 03 October 2016
GET THIS BOOKData Privacy

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

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

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 Data Wrangling

Principles of Data Wrangling
  • Author : Tye Rattenbury,Joseph M. Hellerstein,Jeffrey Heer,Sean Kandel,Connor Carreras
  • Publisher : "O'Reilly Media, Inc."
  • Release : 29 June 2017
GET THIS BOOKPrinciples of Data Wrangling

A key task that any aspiring data-driven organization needs to learn is data wrangling, the process of converting raw data into something truly useful. This practical guide provides business analysts with an overview of various data wrangling techniques and tools, and puts the practice of data wrangling into context by asking, "What are you trying to do and why?" Wrangling data consumes roughly 50-80% of an analyst’s time before any kind of analysis is possible. Written by key executives

Big Data

Big Data
  • Author : Nathan Warren
  • Publisher : Unknown Publisher
  • Release : 07 May 2021
GET THIS BOOKBig Data

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

Applied Biostatistical Principles and Concepts

Applied Biostatistical Principles and Concepts
  • Author : Laurens Holmes, Jr.
  • Publisher : Routledge
  • Release : 22 November 2017
GET THIS BOOKApplied Biostatistical Principles and Concepts

The past three decades have witnessed modern advances in statistical modeling and evidence discovery in biomedical, clinical, and population-based research. With these advances come the challenges in accurate model stipulation and application of models in scientific evidence discovery Applied Biostatistical Principles and Concepts provides practical knowledge using biological and biochemical specimen/samples in order to understand health and disease processes at cellular, clinical, and population levels. Concepts and techniques provided will help researchers design and conduct studies, then translate data

Principles of Data Integration

Principles of Data Integration
  • Author : AnHai Doan,Alon Halevy,Zachary Ives
  • Publisher : Elsevier
  • Release : 25 June 2012
GET THIS BOOKPrinciples of Data Integration

How do you approach answering queries when your data is stored in multiple databases that were designed independently by different people? This is first comprehensive book on data integration and is written by three of the most respected experts in the field. This book provides an extensive introduction to the theory and concepts underlying today's data integration techniques, with detailed, instruction for their application using concrete examples throughout to explain the concepts. Data integration is the problem of answering queries

Principles and Practice of Clinical Research

Principles and Practice of Clinical Research
  • Author : John I. Gallin,Frederick P. Ognibene
  • Publisher : Academic Press
  • Release : 07 May 2021
GET THIS BOOKPrinciples and Practice of Clinical Research

The second edition of this innovative work again provides a unique perspective on the clinical discovery process by providing input from experts within the NIH on the principles and practice of clinical research. Molecular medicine, genomics, and proteomics have opened vast opportunities for translation of basic science observations to the bedside through clinical research. As an introductory reference it gives clinical investigators in all fields an awareness of the tools required to ensure research protocols are well designed and comply

Patterns, Principles, and Practices of Domain-Driven Design

Patterns, Principles, and Practices of Domain-Driven Design
  • Author : Scott Millett,Nick Tune
  • Publisher : John Wiley & Sons
  • Release : 20 April 2015
GET THIS BOOKPatterns, Principles, and Practices of Domain-Driven Design

Methods for managing complex software construction following the practices, principles and patterns of Domain-Driven Design with code examples in C# This book presents the philosophy of Domain-Driven Design (DDD) in a down-to-earth and practical manner for experienced developers building applications for complex domains. A focus is placed on the principles and practices of decomposing a complex problem space as well as the implementation patterns and best practices for shaping a maintainable solution space. You will learn how to build effective