The aim of this research is to design and implement a relational database using a real-world managerial accounting dataset to support financial analysis. The dataset used in this project was obtained from Kaggle (Hassan, 2023) and contains realistic accounting information, including transactions, departments, categories, revenues, and expenses. The project began with cleaning and converting the original Excel file into CSV format to resolve data inconsistencies before importing the data into MySQL Workbench, demonstrating the importance of proper data preparation in accounting systems. A relational database schema was designed using entities such as Departments, Categories, Projects, Locations, Accounts, and Transactions, and an ER diagram was created to illustrate the relationships among these entities. SQL queries were developed to analyze expenses and calculate totals by department, and a stored procedure was implemented to retrieve department-specific transaction data.

The database was then connected to a Java application using JDBC, allowing the stored procedure to be executed from an external program. While challenges were encountered during the Java integration, particularly with connection setup and runtime input, the system successfully demonstrated how relational databases support managerial accounting analysis and decision-making. Future work could expand this system by incorporating additional datasets, advanced analytical queries, enhanced reporting features, and improved user interaction within the Java application to further support managerial decision-making.