The article contains a review of the unique Ukrainian experience of launched and implemented projects in the conditions of a global risk, i. e. the war. It is highlighted that the large-scale invasion of the Russian Federation on the Ukrainian territory caused global threats and risks for public and business organizations and the Ukrainian society as a whole. The emphasis is made on top innovative projects of Ukraine launched and implemented (or being rapidly developed) due to the intensive use of digitalized processes. The authors presented a review of global reforms in the areas of strategic importance for Ukraine: development of road infrastructures in Ukraine, modernization of heath protection sector, reduction of Ukraine’s dependence on energy imports (especially on Russia), development of digitalized processes, improvement of the education quality and bringing the domestic education system in conformity with European standards. These reforms involved the development of megaprojects that could be successfully implemented several years before the beginning of the war and continue to be extensively used in daily activities of Ukrainian citizens. The issue of big data implementation as a useful ground for the successful accomplishment of projects in the conditions of war and the future postwar period is elaborated on.
The article is focused on issues of the secure operation of official statistics in
Ukraine during the application of martial law. It was found that the gaps in
conventional sources of statistical data caused by the war needed to be filled with data
from alternative sources, including Big Data. The level of digitalisation in Ukraine as
the basis for using Big Data was analysed by the proposed indices of internetisation,
social progress and digital transformation. Thanks to our research, several problems
(methodological, legal, financial, and managerial) were identified as vital for
statistical offices on their way to the implementation of Big Data in statistical
processes. Our proposals concern tools for Big Data processing, such as Data Hypercube
as a way for presenting Big Data for their visualisation, applications of Web scraping
in estimating the consumer prices index, analyses of labour and real estate markets, and
the applications of specialised software for the collection, processing and analysis of
Big Data sets.
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