Boost Cafeteria Sales Through Data Mining

Developed a desktop application to streamline inventory management and sales processes for a hardware components shop. This comprehensive tool empowers business administrators to oversee sellers, customers, distributors, products, and inventory with ease. Key features include the ability to create and manage product bundles (combos), allowing administrators to offer special deals and promotions. Additionally, the application enables users to monitor stock levels, generate insightful visualizations and statistics, and automate tasks such as the creation of purchase orders when stock levels reach a specified minimum. These features ensure efficient inventory management and enable informed decision-making to drive business growth.

For enhanced data visualization and deeper insights, a dedicated Power BI report complements this research. This OLAP report provides a comprehensive overview of association rules, meticulously detailing key metrics such as confidence, support, and lift. By visualizing these critical parameters in a user-friendly interface, the Power BI report empowers stakeholders to obtain actionable insights and make informed decisions that drive business success.

• R
• Power BI
• Data Mining
• Association Rules
• Scikit-learn
• Pandas

Here's the link to the research where you can find all the process and results about the research.

This is a video summary about the functionality of the OLAB Cube in PowerBI

You can interact with it if you have PUCMM organization access