Title: Restaurant Orders Dashboard (Power BI)

Description:

Built an interactive Power BI dashboard analyzing 12,000+ restaurant order line items to answer four operational questions: which menu items sell best and worst, what the highest-value orders look like, when order volume peaks throughout the day, and which cuisine category has the strongest case for menu expansion based on demand relative to current item variety.

Modeled relationships between order-level and menu-level tables, built calculated columns for time-based analysis (hour, day of week), and used DAX measures to compare order volume against menu size per cuisine category, surfacing that American cuisine has the highest orders-per-item ratio across the menu, a clear signal for where to expand.

While validating the results against raw data, caught and fixed a modeling bug where duplicate items within a single order were being undercounted in a grouped visual, corrected by restructuring the aggregation as an explicit measure rather than an implicit cross-table sum.

Full breakdown and dashboard file available on GitHub: https://github.com/aiman-ami/restaurant-orders-dashboard

Skills: Power BI, DAX, Data Modeling, Data Visualization, Python (validation)