Development of a database for efficient management of gas stations

Background. Modern gasoline stations face a number of challenges related to data management, inventory accounting, and customer service. Traditional accounting and management methods are often inefficient, resulting in increased time spent on processing information and an increased likelihood of errors. The lack of a centralized system for storing and processing data makes it difficult to analyze sales and manage inventory, which negatively affects the overall efficiency of the station.

Creating a database for a gas station solves these problems by providing automation of accounting, inventory management and customer service processes. The database allows centralized storage of information on sales, customers, fuel and financial transactions, which greatly simplifies data access and processing.

Purpose. The objective is to develop a tool that will provide automation of accounting and management at a filling station, including storage of information on customers, fuel and transactions, as well as support for analytics to make informed management decisions. This will increase the efficiency of the station, improve customer service and reduce the likelihood of accounting errors.

Method and methodology. To develop the gas station database, the Java programming language was used to create the interface and application logic, and PostgreSQL was used to store and manage the data. The approach was based on the use of a relational data model, which ensures the reliability, integrity and scalability of the system.

Results. The database supports storage of customer, fuel, sales and financial transaction information. Data is centrally managed in PostgreSQL, allowing easy operations for creating, editing and deleting records. The system also includes functions to analyze the data to facilitate informed management decisions. The database architecture provides modularity, allowing new functions to be added without significant changes to existing code.

Scope of the results.  The developed database can be used in the management of gas stations, for automation of accounting and customer service processes, as well as in analytics to improve the efficiency of business processes.

Conclusions. The created database significantly simplifies data management at the gasoline station, reduces the probability of errors and increases the overall efficiency of work. Automation of accounting and customer service processes saves time and resources.