Specialized software platform for analysis of information in data stores

This article presents the design, development, and evaluation of a specialized program for analyzing, developing aggregations of this data, and visualizing large volumes of data. The main goal of this program is to simplify data processing, speed up their analysis, and make it easier to write code for problems with large amounts of data. To achieve this goal, machine learning is used, as well as two repositories.

The program includes a convenient and easy-to-understand interface, servers that process various types of requests from users and transfer them to the database, and the database itself with two repositories.

The research methodology used in this study involves a thorough analysis of existing programs and methods for solving problems with large volumes of data. This analysis informed the design of the core features of the program, which were then subjected to extensive testing and evaluation. A user study was conducted to evaluate the effectiveness of programs with machine learning in comparison to programs that work without it, and a comparison of the speed of implementations of program development and data processing was conducted.

The results of the study show that this approach has accelerated program development, accelerated data processing, and made it more qualitative and accurate. The study concludes that the platform has significant potential to improve the performance of large businesses and that with the growth of multiple times of data and technology, without using this, the development of programs with similar logic will be completely ineffective.