Data mining is a challenging process that involves finding patterns in massive data sets using techniques that combine machine learning, statistics, and database systems. Many companies utilize it for optimizing operations and production. Another factor that is crucial for most organizations is the decision-making process. This was also very important for Agiliway’s client, who works in the fintech sector.
In this article, we are taking a closer look at the project, including its goal, the key tasks performed by the specialists, and the challenges they overcame during the work. And finally, what result the solution brings to the client.
Background of the Project
One of the largest fintech companies asked Agiliway to develop a full-featured information and analytical system for tracking decision-making processes based on relevant documents and statistics. Thanks to this service, the company’s management can not only check the correctness of the decision, but also understand what information is more important in the process of making it.
The company’s developers, with extensive Big Data and business intelligence experience, have created a comprehensive FinTech solution consisting of SQL databases and a highly responsive interface built on React.
To develop a successful Software-as-a-Service (SaaS) solution for financial institutions, the firm required a data visualization and analysis solution that is both adaptable and scalable. Additionally, the solution needed to include comprehensive security management capabilities and an exceptional user interface (UI) that enables dynamic aggregation, mining, grouping, and regrouping of data.
The project’s specific requirements precluded the use of readily available visualization tools, such as Tableau. To achieve the objective of the project, Agiliway was required to:
- construct a BI system that would enable the viewing of vast volumes of information using data kept in MS SQL databases.
- create dynamic charts and reports on the platform.
- permit financial organizations to control who has access to their private information and to monitor user records.
With a robust background in Big Data, business intelligence, and data visualization, Agiliway promptly implemented the proposed solution by effectively using JS frameworks.
The platform’s architecture encompasses:
Back-end: API implementation utilizing MS.NET and MS SQL databases.
Front-end: A data analysis application built using React that displays results in the form of dynamic charts.
The charts may depict studies of institutions’ Big Data from a variety of angles, such as:
- What and how many nodes were the sources of information for the selected node (input), and what sources utilize the information from this node;
- The frequency and timing of use of a certain information source, such as the season of the year or stage of decision-making, are of interest.
- The cost-value analysis pertaining to a certain node.
- In the course of their job, different departments often use distinct nodes.
Agiliway has created a sophisticated user management and security system to guarantee the confidentiality of financial institutions’ data. In this manner, it becomes feasible to generate novel users, administer their privileges in relation to accessing certain reports and information sources, and monitor all records to ascertain which reports were perused and by which individuals.
An intelligently designed user interface serves as a valuable supplement to visualization and enhances the process of analysis. An illustration of the node presents relevant information when hovering over it with a mouse, while distinct colors are used to facilitate the identification of various types of information sources, such as applications, databases, FTP, email, and Excel files.
Value Delivered to the Client
Agiliway’s proficiency in Big Data and business intelligence allows to provide a multifaceted fintech solution that encompasses SQL databases and a highly efficient and rapid front-end interface developed using React.
The system has garnered significant recognition from both users and financial institutions. It has been effective in assisting financial institutions in assessing the value of information and calculating key performance indicators for workers and departments. This is achieved via analyzing the use and interpretation of available data.
The FinTech business has successfully established itself in the market and is seeing sustained revenue growth due to its ownership of a platform that is adaptable, scalable, and secure.