ANALYSIS OF METHODS FOR ASSESSING THE BIG DATA INFORMATIVITY
S.V. Maltseva1, V.B. Barakhnin2,3, P.V. Golubtsov4, M.N. Kalimoldaev3
1National Research University “Higher School of Economics”, Moscow, Russia
2Federal Research Center for Information and Computational Technologies, Novosibirsk, Russia
3Institute of Information and Computational Technologies, Almaty, Kazakhstan
4Lomonosov Moscow State University, Moscow, Russia
Keywords: informativity, big data, big data informativity, information space, information value metrics
Abstract
Assessing the big data informativity is a topical area of research related to realizing the potential of big data technology for solving problems of automated monitoring, forecasting, decision-making, and machine learning in economic sectors. This article analyzes modern approaches and methods defining the concept of informativity and allowing for assessing the informativity in the context of the pragmatic and relativity of information, its value, and usefulness. The specifics of processing distributed and streaming big data and determining the minimum information space are considered. Assessing the big data informativity for problems of feature generation and selection, design, and data-driven management are discussed in detail.
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