METHODOLOGICAL ASPECTS OF PROVIDING THE DISCIPLINE "INFORMATION AND ANALYTICAL TECHNOLOGIES IN BUSINESS" FOR UNDERGRADUATES IN THE DIRECTION OF "ECONOMICS"

Relevance. Nowadays, most companies use the data accumulated in the enterprise information system to solve corporate governance problems. The most modern means for operational data processing are information and analytical systems, therefore, the task of studying the peculiarities of training undergraduates in the use of information and analytical systems technologies is relevant.

Aim. The purpose of the work is to identify the peculiarities of studying the technologies of information and analytical systems by masters of the "Economics" direction in the conditions of use by modern companies of the "data-driven" approach.

Methodology. During the study, methods of analyzing professional and educational standards, educational programs of disciplines of higher educational institutions, the content of advanced training courses on the development and use of information and analytical systems, scientific, educational, methodological and educational literature for universities were used.

Scientific novelty / theoretical and / or practical significance. Methodological recommendations for conducting classroom laboratory classes using software tools for the implementation of information and analytical systems have been developed. Examples of assessment tools for monitoring students are given.

Results of the research. Presented the experience of teaching the discipline "Information and analytical technologies in business" to undergraduates in the direction of "Economics." The goals and objectives of the course in the framework of economic education are indicated, the importance of obtaining skills in working with information and analytical systems by masters in the direction of "Economics" is justified. The peculiarities of the organization of the process of studying the discipline are indicated.

Conclusions. The article summarizes the practical experience of training undergraduates in the use of information and analytical systems technologies. When conducting classroom laboratory work, it is necessary to solve practical problems using modern means of implementing information and analytical systems, it is important to use software products without violating licensing requirements.

1. Akimkin Je.Je., Abbasov Je.M., Nguen K.T. Obuchenie osnovam operativnogo analiza dannyh // Innovacionnye tehnologii v sovremennom obrazovanii. Sbornik materialov VI Mezhdunarodnoj nauchno-prakticheskoj internet-konferencii. - 2019. - S. 19-27.

2. Bajumova M.V., Kartasheva O.V. Analiticheskie vozmozhnosti sovremennyh informacionnyh sistem kak instrument cifrovizacii korporativnogo upravlenija // Cifrovye tehnologii v social'no-jekonomicheskom razvitii Rossii: vzgljad molodyh: sbornik statej i tezisov dokladov XVI nacional'noj nauchno-prakticheskoj konferencii studentov, magistrantov i aspirantov s mezhdunarodnym uchastiem (18 fevralja 2020 g.). - Ural'skij filial Finuniversiteta. - Moskva: Izdatel'stvo «Pero», 2020. - S. 493-496.

3. Berezhnaja O.V., Berezhnaja E.V. Metodicheskie voprosy primenenija informacionno-analiticheskih i statisticheskih sistem v obuchenii // Sovremennoe srednee professional'noe obrazovanie. 2020. № 2. S. 21-23.

4. Bogomolova E.V. Sistema obuchenija magistrov istorii discipline "Informacionnye tehnologii v prognozno-analiticheskoj dejatel'nosti" // Vestnik Rjazanskogo Gosudarstvennogo Universiteta imeni S.A. Esenina. 2014. № 3(44). S. 7-14.

5. Bokov I.S. Data-driven podhod k upravleniju: delo ne tol'ko v dannyh // Reformy v Rossii i problemy upravlenija - 2020. Materialy 35-j Vserossijskoj nauchnoj konferencii molodyh uchenyh. 2020. S. 129-132.

6. Grigor'eva Ju.O., Kuz'mina M.D., Tarasova A.Ju Osobennosti formirovanija cifrovoj sredy v rossijskom bankovskom sektore // Molodaja nauka - 2021. Sbornik materialov XII nacional'noj nauchno-prakticheskoj konferencii molodyh uchjonyh, aspirantov i studentov. 2021. S. 35-39.

7. Zvjagin K.A., Juzdova L.P., Ermakova E.N. Informacionnye tehnologii v podgotovke bakalavra, magistra i specialista zaochnoj formy obuchenija // Vestnik Juzhno-Ural'skogo gosudarstvennogo gumanitarno-pedagogicheskogo universiteta. 2021. № 1 (161). S. 111-128.

8. Kartasheva O.V. Primenenie vitrin statisticheskih dannyh Federal'noj sluzhby gosudarstvennoj statistiki pri izuchenii operacij s OLAP-kubom // Intellektual'nyj potencial obrazovatel'noj organizacii i social'no-jekonomicheskoe razvitie regiona: sbornik materialov mezhdunarodnoj nauchno-prakticheskoj konferencii Akademii MUBiNT. Jaroslavl': Obrazovatel'naja organizacija vysshego obrazovanija (chastnoe uchrezhdenie) «Mezhdunarodnaja akademija biznesa i novyh tehnologij (MUBiNT)», 2020. S. 167-170.

9. Kartasheva O.V. Umenie rabotat' s informacionno-analiticheskimi sistemami kak odna iz professional'nyh kompetencij studenta po napravleniju podgotovki «Jekonomika» (uroven' magistratury) // Intellektual'nyj potencial obrazovatel'noj organizacii i social'no-jekonomicheskoe razvitie regiona. Sbornik materialov mezhdunarodnoj nauchno-prakticheskoj konferencii Akademii MUBiNT. Mezhdunarodnaja akademija biznesa i novyh tehnologij. 2022. S. 218-221.

10. Korneeva O.D. Cifrovye navyki kak vazhnaja komponenta upravlencheskoj kompetentnosti budushhego menedzhera // Vestnik Moskovskogo gosudarstvennogo oblastnogo universiteta. Serija: Pedagogika. 2021;(3):117-124. https://doi.org/10.18384/2310-7219-2021-3-117-124

11. Kravchenko T.K. Podgotovka specialistov v oblasti biznes-analitiki: opyt fakul'teta biznes-informatiki GU-VShJe // Biznes-informatika. 2010. №4(14). S. 54-59.

12. Mitjaeva A. M., Ibrahim A. A. Formy kontrolja znanij studentov vuzov v uslovijah distancionnogo obuchenija // Vestnik Moskovskogo gosudarstvennogo oblastnogo universiteta. Serija: Pedagogika. 2021. № 4. S. 161–172. DOI: 10.18384/2310-7219-2021-4-161-172

13. Sannikova N.I., Kutyshkin A.V., Savina T.V. Ob ispol'zovanii informacionnyh tehnologij pri formirovanii biznes-analiticheskih kompetencij bakalavrov jekonomiki // Innovacii v obrazovanii. 2018. №9. S. 116-130.

14. Solodchenko E. E., Edel'kina A. Prinjatie reshenij na osnove data-driven podhoda // Innovacii. Nauka. Obrazovanie. - 2021. - № 37. - c. 1038-1043.

15. Tarasova A.Ju. Informacionnoe obespechenie finansovogo menedzhmenta transnacional'nyh korporacij i bankov na osnove tehnologii Big Data // Sbornik nauchnyh statej nauchno-pedagogicheskih i prakticheskih rabotnikov / kol. avtorov; pod red. V.A. Nekljudova i O.V. Kartashevoj. – Jaroslavl': Kancler, 2016. S. 253-255.

16. Adelmo ELOY, Camila F. ACHUTTI, Cassia FERNANDEZ, Roseli de DEUS LOPES, A data-driven approach to assess computational thinking concepts based on learners’ artifacts, Informatics in Education(2021), DOI 10.15388/infedu.2022.02

17. Belcastro, L., Cantini, R., Marozzo, F. et al. Programming big data analysis: principles and solutions. J Big Data 9, 4 (2022). https://doi.org/10.1186/s40537-021-00555-2

18. Boutkhoum, O., Hanine, M. An integrated decision-making prototype based on OLAP systems and multicriteria analysis for complex decision-making problems. Appl Inform 4, 11 (2017). https://doi.org/10.1186/s40535-017-0041-6

19. Ilko Kovacic, Christoph G. Schuetz, Bernd Neumayr, Michael Schrefl, OLAP Patterns: A pattern-based approach to multidimensional data analysis, Data & Knowledge Engineering, Volume 138, 2022, 101948, ISSN 0169-023X, https://doi.org/10.1016/j.datak.2021.101948.

20. Mohsen Dorodchi, Nasrin Dehbozorgi, Mohammadali Fallahian, Seyedamin Pouriyeh, Teaching Software Engineering using Abstraction through Modeling, Informatics in Education 20(2021), no. 4, 515-532, https://doi.org/10.15388/infedu.2021.23