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Al-Mashawi — Restaurant Operations Management System
Overview
Al-Mashawi is a portfolio project demonstrating how a restaurant's operational information can be organized into one connected Notion system.
The goal was to create a centralized workspace for managing recurring operational information while improving visibility across different areas of the business.
Business Context
A restaurant manages many interconnected areas at the same time — from menus and recipes to suppliers, schedules, team information, checklists, goals, and reporting.
The system was designed to bring these areas together into a more structured operational workspace.
System Areas
The workspace includes:
Operations Dashboard
Menu Management
Chef Directory
Recipe Management
Supplier Management
Weekly Scheduling
Customer Reviews
Opening & Closing Checklists
Monthly Goals
Weekly P&L Reporting
Team Directory
Workspace Documentation
Approach
The system was structured around the relationship between operational information rather than treating each area as an isolated page.
The goal was to create a practical operating hub where recurring information could be easier to access, maintain, and manage.
Outcome
The result is a centralized restaurant management workspace that connects day-to-day operational information into one organized system.
Project Type
Portfolio / Demonstration Project
Created to demonstrate Business Operations, Workflow Design, Database Architecture, and Notion system-building capabilities.
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AI-Assisted Sales Intelligence Dashboard
Project Overview
This project is an end-to-end Sales Analytics solution built using Python, SQL, and Power BI.
The workflow includes:
Data Cleaning using Python (Pandas)
Data Storage using SQLite
Business Analysis using SQL Queries
Interactive Dashboard using Power BI
Automated Business Report Generation using Python
The goal of this project is to analyze sales performance, identify profitable products, monitor regional performance, and generate business recommendations.
Dataset
Dataset: Sample Superstore Dataset
Records: 9,994
Features:
Order Details
Customer Information
Product Information
Sales
Profit
Discount
Region
Category
Sub-Category
Tools & Technologies
Python
Pandas
SQLite
SQL
Power BI
Data Visualization
Business Intelligence
Project Workflow
CSV Dataset
↓
Data Cleaning (Python)
↓
SQLite Database
↓
SQL Analysis
↓
Power BI Dashboard
↓
AI Business Report
Dashboard Pages
Executive Overview Total Sales Total Profit Total Orders Profit Margin Regional Sales Analysis Category Performance Analysis
Product Performance Analysis Top Profitable Products Loss-Making Products Profit by Category Sales by Sub-Category
Sales Trends Analysis Sales Trends Over Time Profit Trends Seasonal Performance Insights Key Business Insights West Region generated the highest sales. Technology is the most profitable category. Several products generate significant losses and require pricing review. Sales performance varies significantly across regions. Automated AI Report The project includes a Python-based reporting system that automatically generates:
Total Sales
Total Profit
Business Insights
Strategic Recommendations
Author
Gourav Jangid
Aspiring Data Analyst
Open to Data Analytics Opportunities
Designed and developed a modern restaurant website focused on showcasing the menu, highlighting the dining experience, and making table reservations easy. The site features an engaging visual design, responsive layout, and clear calls-to-action to improve customer engagement.
Making reservations easy is the right focus for a restaurant site.
🍳 Darakai Live Kitchen — Reimagining Food Delivery
What if customers didn't have to simply wait for their food?
I designed Darakai Live Kitchen, a new concept for the Darakai Food Delivery app that lets customers watch their food being prepared live by the chef.
Instead of a simple “Preparing your order” status, customers can:
🔴 Watch the kitchen live
💬 Interact with the chef
❤️ Send reactions
🍽️ Follow the cooking → plating → ready journey
🚴 Track the transition from kitchen to delivery
On the restaurant side, chefs get a dedicated Kitchen Dashboard to manage orders, start a live cooking session, communicate with customers, and end the stream when the order is ready.
The experience
Order → Confirmed → Cooking Live → Plating → Ready → Pickup → Delivered
The idea is to transform food delivery from a simple transaction into a more transparent, engaging, and human experience.
Technical direction
The concept is designed around a Flutter customer app + restaurant interface + .NET API, with real-time video handled by dedicated streaming infrastructure while the backend manages orders, live sessions, permissions, chat, notifications, and session status.
More than delivery. A closer connection.
#Flutter #DotNet #FoodDelivery #UXDesign #ProductDesign #LiveStreaming #MobileApp #Darakai
If the kitchen stream drops, will the order timeline stay visible? Customers could still follow their order while the video is unavailable.