Formation of digital databases in monitoring of realization of educational-intellectual potential of the regions of Ukraine

Authors

DOI:

https://doi.org/10.15587/2706-5448.2022.256570

Keywords:

digital database, educational and intellectual potential, labor markets, data mining, technically correct data

Abstract

The object of research is databases of graduates of educational institutions that need to be digitalized and prepared for analysis. The study highlights the formation of a digital database out of the graduates among educational institutions for monitoring the implementation of educational and intellectual potential. Monitoring procedures for tracking the implementation of educational and intellectual potential are an important component of making managerial decisions to balance supply and demand in professional labor markets, make better use of the human potential of economic development, and reform educational institutions in accordance with the latest public needs. Monitoring procedures for tracking the employment of graduates are an important element of Education Management. The study highlights the technology of preparing and forming databases of graduates of educational institutions for further work with them (conducting a survey, summarizing and visualizing its results) using Microsoft Excel. For this purpose, methods of intelligence analysis of data, ranking and classification of statistical populations, and data mining technologies are used. Approaches to structuring and coding graduate data are described. The mechanism for creating a digital database is provided with arguments and descriptions of all the structural components of the database: fields, headers, and records. The description of the sequence and results of working with databases is given on the example of data from graduates of higher educational institutions of the Lviv region. These technologies for working with databases were obtained during the implementation of the regional development project within the framework of EU sectoral support, which was implemented in the Lviv region (Ukraine) in 2018–2020 with the participation of the authors. The proven method of forming digital databases highlighted in the study is only a stage of monitoring the implementation of the educational and intellectual potential of graduates of educational institutions of the Lviv region. Method can be used and scaled to other regions of Ukraine without significant changes or to educational institutions of different levels with minor clarifications. At the same time, the creation of such databases at the national level would increase the effectiveness of monitoring the employment of graduates. The proposed methodology is universal and allows for national research, as well as provides opportunities for international comparisons of educational and intellectual potential.

Author Biographies

Ulіana Sadova, Lviv Polytechnic National University

Doctor of Economic Sciences, Professor

Department of Theoretical and Applied Economics

Tetiana Stepura, Lviv Polytechnic National University

Doctor of Economic Sciences, Associate Professor

Department of Theoretical and Applied Economics

Olga Korytska, Lviv Polytechnic National University

PhD, Assistant

Department of Theoretical and Applied Economics

References

  1. Monitorynh realizatsii intelektualnoho potentsialu vypusknykiv zakladiv vyshchoi ta profesiino-tekhnichnoi osvity prykordonnoho rehionu: sotsialne partnerstvo, derzhavne i rehionalne zamovlennia. IntellectLviv. Available at: https://intellectlviv.com/site/zpto
  2. Provost, F., Fawcett, T. (2013). Data Science for Business: What You Need to Know About Data Mining and Data-Analytic Thinking. Sebastopol: O’Reilly, 385.
  3. Pyle, D. (1999). Data Preparation for Data Mining. Morgan Kaufmann. Available at: https://www.temida.si/~bojan/MPS/materials/Data_preparation_for_data_mining.pdf
  4. Jonge, E. de, Loo, M. van der (2013). An introduction to data cleaning with R. Statistics Netherlands. Available at: https://cran.r-project.org/doc/contrib/de_Jonge+van_der_Loo-Introduction_to_data_cleaning_with_R.pdf
  5. What Is a Database? Database defined. Oracle Cloud Infrastructure. Available at: https://www.oracle.com/database/what-is-database/
  6. Nishtha, J., Sahil, P., Mehak, A., Ishita, K., Dishant, G. A. (2012). Survey and Comparison of Relational and Non-Relational Database. International Journal of Engineering Research & Technology, 1 (6), 1–5.
  7. Radoev, M. (2021). Contemporary Trends in the Development of Databases. Ikonomiceski i Sotsialni Alternativi, 1, 5–15.
  8. Marets, O., Sysan, O. (2021). On data preparation for analysis in socio-economic research. Visnyk of the Lviv University. Series Economics, 61. Available at: http://publications.lnu.edu.ua/bulletins/index.php/economics/article/view/11418
  9. Vries, G. de, Arfelt, L., Drees, D., Godemann, M., Hamilton, C., Jessen-Thiesen, B. et. al. (2021). The Economic Transformation Database (ETD): content, sources, and methods. WIDER TECHNICAL NOTE, 2, 105. doi: http://doi.org/10.35188/unu-wider/wtn/2021-2
  10. Hrynkevych, O. S., Sadova, U. Ya., Levytska, O. O. (2020). International experience in monitoring graduates’ employment and ways of its application in Ukraine. Demography and Social Economy, 1 (35), 126–138.
  11. Mariza, M. (2015). Advanced spread sheets – Microsoft Excel 2010. Open society for idea exchange (ODRAZI). Zagreb, 54. Available at: https://www.infobooks.org/pdfview/6608-advanced-spreadsheets-microsoft-excel-2010-mariza-maini/
  12. Davenport, J. H., Grant, J., Jones, C. M. (2020). Data Without Software Are Just Numbers. Data Science Journal, 19 (1). doi: http://doi.org/10.5334/dsj-2020-003
  13. Meyer, D. Z., Avery, L. M. (2008). Excel as a Qualitative Data Analysis Tool. Field Methods, 21 (1), 91–112. doi: http://doi.org/10.1177/1525822x08323985
  14. Microsoft Excel Manual (2015). University of Mary Washington. Ver. 1, 44. Available at: https://adminfinance.umw.edu/tess/files/2013/06/Excel-Manual1.pdf
  15. Reiestr subʼiektiv osvitnoi diialnosti. Zaklady vyshchoi osvity. Available at: https://registry.edbo.gov.ua/
  16. Pro vnesennia zmin do pereliku haluzei znan i spetsialnostei, za yakymy zdiisniuietsia pidhotovka zdobuvachiv vyshchoi osvity (2021). Postanova Kabinetu Ministriv Ukrainy No. 762. 07.06.2021. Available at: https://www.kmu.gov.ua/npas/pro-vnesennya-zmin-do-pereliku-galuzej-znan-i-specialnostej-za-yakimi-zdijsnyuyetsya-pidgotovka-zdobuvachiv-vishchoyi-osviti-i070721-762

Downloads

Published

2022-04-30

How to Cite

Sadova, U., Stepura, T., & Korytska, O. (2022). Formation of digital databases in monitoring of realization of educational-intellectual potential of the regions of Ukraine. Technology Audit and Production Reserves, 2(4(64), 28–32. https://doi.org/10.15587/2706-5448.2022.256570

Issue

Vol. 2 No. 4(64) (2022): Economics of enterprises. Macroeconomics

Section

Development of Productive Forces and Regional Economy: Original Research

License

Copyright (c) 2022 Ulіana Sadova, Tetiana Stepura, Olga Korytska

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

The consolidation and conditions for the transfer of copyright (identification of authorship) is carried out in the License Agreement. In particular, the authors reserve the right to the authorship of their manuscript and transfer the first publication of this work to the journal under the terms of the Creative Commons CC BY license. At the same time, they have the right to conclude on their own additional agreements concerning the non-exclusive distribution of the work in the form in which it was published by this journal, but provided that the link to the first publication of the article in this journal is preserved.