THE USE OF THE CLOUD-BASED SERVICES OF DATA PROCESSING WITHIN THE SYSTEMS OF OPEN SCIENCE
DOI:
https://doi.org/10.14308/ite000692Keywords:
Cloud technologies, Office 365, open science, Power BI, processing of research results, research institutions, researchersAbstract
The paper analyzes the possibilities and justifies the feasibility of using and implementing cloud data processing services in the activities of a scientist and a research or educational institution unit. Objectives of the study: to outline the prospects and modern European trends in the use of cloud services in open systems of scientific research; Describe how to use Power BI services as a component of Office 365 in the activities of a scientist and analyze existing licensed offers of Power BI; generalize the experience of using the services of a cloud-based environment in the activities of a scientist and a scientific or educational institution. The object of research is: the process of processing data in open systems of scientific research. The subject of the study is: the use of cloud data processing services in supporting the activities of a scientist and a research institution.
Research methods: analysis of documentation from the official site Power BI, observation, comparison, conversations with representatives of the company BIJB by the Center of competence of BI, analysis of existing experience of use, synthesis of the results of scientific and experimental research. In this paper, the features of using Power BI as a tool of Office 365 in comparison with traditional table processors are considered. A comparative analysis of the existing types of licensing that can be used in the activities of a scientist or a research research unit is conducted. The possibilities of using the free Desktop Licensing, which will be sufficient to cover the main and intermediate results of a scientist or research unit unit, are outlined. The feasibility of using and implementing Power BI as a tool of Office 365 is substantiated for the processing of quantitative and qualitative research results. Conclusions and recommendations: Using Desktop Power BI to process the results of an experimental study by a scientist will be quite enough. However, the Desktop Power BI functionality will be quite limited and not sufficiently adaptive to the work of a group of scientists in the research unit.
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Shyshkina, M. (2017). The General Model of the Cloud-based Learning Environment of Educational Personnel Training. Teaching and Learning in a Digital World. ICL 2017. Advances in Intelligent Systems and Computing, Vol. 715.
Shyshkina, M. (2015). The Hybrid Service Model of Electronic Resources Access in the Cloud-Based Learning Environment. CEUR Workshop Proceedings, Vol.1356, 295-310.
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