TY - UNPB
T1 - The analysis of big data on cites and regions - Some computational and statistical challenges
AU - Schintler, Laurie A.
AU - Fischer, Manfred M.
PY - 2018/10/28
Y1 - 2018/10/28
N2 - Big Data on cities and regions bring new opportunities and challenges to data analysts and city planners. On the one side, they hold great promise to combine increasingly detailed data for each citizen with critical infrastructures to plan, govern and manage cities and regions, improve their sustainability, optimize processes and maximize the provision of public and private services. On the other side, the massive sample size and high-dimensionality of Big Data and their geo-temporal character introduce unique computational and statistical challenges. This chapter provides overviews on the salient characteristics of Big Data and how these features impact on paradigm change of data management and analysis, and also on the computing environment.
AB - Big Data on cities and regions bring new opportunities and challenges to data analysts and city planners. On the one side, they hold great promise to combine increasingly detailed data for each citizen with critical infrastructures to plan, govern and manage cities and regions, improve their sustainability, optimize processes and maximize the provision of public and private services. On the other side, the massive sample size and high-dimensionality of Big Data and their geo-temporal character introduce unique computational and statistical challenges. This chapter provides overviews on the salient characteristics of Big Data and how these features impact on paradigm change of data management and analysis, and also on the computing environment.
U2 - 10.57938/c8b290a6-a690-44d4-8c33-501d3c696f21
DO - 10.57938/c8b290a6-a690-44d4-8c33-501d3c696f21
M3 - WU Working Paper
T3 - Working Papers in Regional Science
BT - The analysis of big data on cites and regions - Some computational and statistical challenges
PB - WU Vienna University of Economics and Business
CY - Vienna
ER -