Big Data for Regional Science

This book PDF is perfect for those who love Business & Economics genre, written by Laurie A Schintler and published by Routledge which was released on 07 August 2017 with total hardcover pages 527. You could read this book directly on your devices with pdf, epub and kindle format, check detail and related Big Data for Regional Science books below.

Big Data for Regional Science
Author : Laurie A Schintler
File Size : 40,8 Mb
Publisher : Routledge
Language : English
Release Date : 07 August 2017
ISBN : 9781351983259
Pages : 527 pages
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Big Data for Regional Science by Laurie A Schintler Book PDF Summary

Recent technological advancements and other related factors and trends are contributing to the production of an astoundingly large and rapidly accelerating collection of data, or ‘Big Data’. This data now allows us to examine urban and regional phenomena in ways that were previously not possible. Despite the tremendous potential of big data for regional science, its use and application in this context is fraught with issues and challenges. This book brings together leading contributors to present an interdisciplinary, agenda-setting and action-oriented platform for research and practice in the urban and regional community. This book provides a comprehensive, multidisciplinary and cutting-edge perspective on big data for regional science. Chapters contain a collection of research notes contributed by experts from all over the world with a wide array of disciplinary backgrounds. The content is organized along four themes: sources of big data; integration, processing and management of big data; analytics for big data; and, higher level policy and programmatic considerations. As well as concisely and comprehensively synthesising work done to date, the book also considers future challenges and prospects for the use of big data in regional science. Big Data for Regional Science provides a seminal contribution to the field of regional science and will appeal to a broad audience, including those at all levels of academia, industry, and government.

Big Data for Regional Science

Recent technological advancements and other related factors and trends are contributing to the production of an astoundingly large and rapidly accelerating collection of data, or ‘Big Data’. This data now allows us to examine urban and regional phenomena in ways that were previously not possible. Despite the tremendous potential of

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