The Analysis of Big Data on Cites and Regions - Some Computational and Statistical Challenges
Laurie A. Schintler and
Manfred Fischer ()
No 2018/08, Working Papers in Regional Science from WU Vienna University of Economics and Business
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.
Keywords: massive sample size; high-dimensional data; heterogeneity and incompleteness; data storage; scalability; parallel data processing; visualization; statistical methods (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-big, nep-cmp, nep-geo, nep-pay and nep-ure
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Persistent link: https://EconPapers.repec.org/RePEc:wiw:wus046:6637
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