

Implementation of Shop ERP System
Abstract
Enterprise Resource Planning (ERP) systems play a crucial role in the efficient management of modern retail businesses, enabling seamless control over inventory, sales, customer data, and financial transactions. This project presents an advanced and comprehensive Shop ERP system, integrating various modules for inventory tracking, billing, customer management, and business intelligence reporting. By utilizing Power BI for interactive visualization, SQL for database management, and Python for data processing, the system provides real-time analytics and automation to optimize retail operations. The research focuses on building a scalable, robust, and user-friendly ERP solution tailored for retail businesses. Additionally, the system incorporates machine learning capabilities to enhance predictive analytics, improving decision-making and operational efficiency.
References
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Zhang, J., et al. (2024). "Machine Learning Models for ERP Systems: Enhancing Forecasting and Fraud Detection." International Journal of Advanced Technologies in Retail, 14(2), 102-118.
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Wang, L., et al. (2023). "Automated Billing Systems in ERP for Retail: Case Study on Reducing Errors." International Journal of Automation and Retail Systems, 9(2), 33-47
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