Spatial Statistics in the Context of Big Data
YU.P. VORONOV1,2
1OOO Korpus, 1, Gorsky microdistrict, Novosibirsk, 630089, Russia
2Institute of Economics and Industrial Engineering, Siberian Branch of the Russian Academy of Sciences, 17, Ac. Lavrentiev av., Novosibirsk, 630090, Russia
Keywords: большие данные, демография, геолокация, социальные сети, посевные площади, спрос на жилье, потребительские цены, big data, demography, geolocation, social media, sown area, demand for housing, consumer prices
Abstract
The article considers the problems of spatial statistics when using big data. It provides examples of changes in foreign practice and the author’s practical joint implementations of statistics and big data. Regional statistics databases are to transform. For instance, a transition will be made from unsold goods price statistics to cash register data. Calculation results on economic-mathematical models are also expected to change. The article concludes with a need to accelerate big data mainstreaming into modeling and Rosstat functions so that model estimations and official statistics would become more useful in practical and research applications.
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