The exponential growth of data in various formats has necessitated efficient methods for data management and integration into relational databases. Traditional approaches to importing data from Excel and CSV files into PostgreSQL can be cumbersome and time-consuming, often requiring intricate coding or manual input. This paper introduces a user-friendly graphical user interface (GUI) application that automates the import process, thereby addressing these challenges. The application allows users to effortlessly select folders containing multiple data files, streamlining the data ingestion process. By employing Python libraries such as Pandas and SQLAlchemy, it facilitates seamless data transfer while ensuring data integrity. Significant benefits include enhanced productivity through automation, reduced human error, and improved accessibility for users with varying technical skills. Ultimately, this tool not only simplifies the workflow for researchers and data analysts but also emphasizes the growing need for effective data handling solutions in an increasingly data-driven world