A. Mukasheva, D. Yedilkhan, M. Aldiyar


The article is devoted to the description of the method of multidimensional database, which is an effective method of data storage, which allows analyzing data qualitatively, and most importantly in a short time. The article discusses the capabilities of multidimensional databases, in particular, multidimensional OLAP (On-Line Analytical Processing) cubes when analyzing large amounts of data. Provides an overview and features of a multidimensional database and discusses the steps you need to take with a multidimensional database to understand the structure and capabilities of an OLAP cube. To create a knowledge base, it describes the steps you can take to create and execute a multidimensional database that you can collect from various sources, save to a database, and then prepare a report using OLAP analysis. Various information system data processing technologies such as OLTP and OLAP were considered. The algorithm of the data storage process for analysis purposes was studied. A model of a multidimensional database in the form of a three-dimensional cube was presented. Examples of analysis and ways of obtaining information from the data cube were also given. The use of a multidimensional database in higher education institutions as a simple and effective method of data storage is considered. There are also illustrations of the structure of a higher educational institution to see the bulkiness of information, and what kind of information database operates in the educational institution.

Ключевые слова

Information system, Database, OLAP, OLTP, three-dimensional, one-dimensional, data analysis

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Karpova I.P. (2009) Osnovy bazy dannyh. Uchebnoe posobie. Moskva: Moscow State Institute of Electronics and Mathematics (Technical University).

Palominos F. E., Córdova, F., Durán, C., & Nuñez, B. (2020). A simpler and semantic multidimensional database query language to facilitate access to information in decision-making. International journal of computers communications and control. 15(4).

Orlova M.A. (2021). Konceptual’noe proektirovanie mnogomernoj bazy dannyh importera produkcii. E-Scio, 11 (62), 99–105.

Blagodatskiy G.A. (2020). Multidimensional database analysis. Izhevsk, Russia: Izhevsk State Technical University named after M. T. Kalashnikov.

Cabibbo, L., & Torlone, R. (1998). A logical approach to multidimensional databases. Lecture Notes in Computer Science, 183–197.

Cabibbo, L., & Torlone, R. (1998). Querying multidimensional databases. Database Programming Languages, 319–335.

Shahi, C., & Sinha, M. (2020). Digital Transformation: Challenges faced by organizations and their potential solutions. International Journal of Innovation Science, 13(1), 17–33.

Iyengar, S. S., Rao, N. S. V., Kashyap, R. L., & Vaishnavi, V. K. (1988). Multidimensional Data Structures: Review and outlook. Advances in Computers, 69–119.

Khatwani, G., & Kar, A. K. (2017). Improving the cosine consistency index for the analytic hierarchy process for solving multi-criteria decision making problems. Applied Computing and Informatics, 13(2), 118–129.

Petersen, A. H., & Ekstrøm, C. T. (2019). Your assistant for documenting supervised data quality screening in R. Journal of Statistical Software, 90(6).

Liu Y.A., Stoller S.D. Knowledge of Uncertain Worlds: Programming with Logical Constraints. - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 11972, (pp.111-127).

Jennex, M. E. (2017). Big Data, the internet of things, and the revised knowledge pyramid. ACM SIGMIS Database: the DATABASE for Advances in Information Systems, 48(4), 69–79.

Zhang, Y., Lin, G., Gu, H., Zhuang, F., & Wei, G. (2020). Multi-copy dynamic cloud data auditing model based on IMB Tree. Enterprise Information Systems, 15(2), 248–269.

Arnas, D., & Rodríguez, M. (2020). Range searching in multidimensional databases using navigation metadata. Applied Mathematics and Computation, 386, 125510.

Anshari, M., Almunawar, M. N., Lim, S. A., & Al-Mudimigh, A. (2019). Customer relationship management and Big Data enabled: Personalization & Customization Of Services. Applied Computing and Informatics, 15(2), 94–101.

Vial, G. (2019). Understanding digital transformation: A review and a research agenda. The Journal of Strategic Information Systems, 28(2), 118–144.

Roberts, N., Qahri-Saremi, H., & Vijayasarathy, L. R. (2021). Understanding IT value at the managerial level: Managerial ambidexterity, seizing opportunities, and the moderating role of information systems use. ACM SIGMIS Database: the DATABASE for Advances in Information Systems, 52(3), 39–55.



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