Operational (Online) Analytics: New Technologies and Opportunities

The aim of the article is to systematise and generalise new knowledge on operational ana­lytics and consider specific automated information systems in terms of the present and prospects for its development. The research methodology was based on the general scientific principles of unity of theory and practice, systematics, complexity, and comprehensiveness of knowledge. The use of general scientific (description, analysis, synthesis, comparison, generalisation) and special (bibliograph­ic, sample observation, grouping, content analysis) methods at the empirical and theoretical lev­els of research contributed to achieving this goal. The scientific novelty of the study is to generalise and systematise new and available knowledge on operational analytics in terms of present and prospects for its development within one study. Conclusions. The case of the International Business Machines Corporation American elec­tronic corporation (pronounced IBM, also known as IBM or «Blue Giant»), one of the world’s largest manufacturers of all types of computers and software, one of the largest providers of global information networks, the author described and analysed the species diversity and fea­tures of the use of automated information and analytical systems based on artificial intelligence, which are available today to many users, and tomorrow will become a daily reality for any com­pany. The information systems and products that IBM now offers to the Ukrainian consumer are briefly described: systems designed for analytics by areas of application; Big Data analysts; data visualisation; policy analytics; data integration systems; advanced analytics products; in­formation systems of advanced analytics based on the Internet of Things; automated systems for forecasting analytics. Attention is focused on the features and benefits of operational analytics and its capabilities in the practical plane of use. The expediency of applying certain automated information systems according to the sphere of activity and stages of information analysis is substantiated. The advantages and prospects of operational (online) analytics development in data analytics are considered.