Телеграм канал «Data Analytics Projects - SQL, Excel, Tableau, Python & Power BI Interview Resources»

🚀𝗠𝗔𝗦𝗧𝗘𝗥 𝗘𝗫𝗖𝗘𝗟 𝗙𝗢𝗥 𝗙𝗥𝗘𝗘 𝗜𝗡 𝟮𝟬𝟮𝟲! 📊

Discover 4 FREE Websites to learn Microsoft Excel from beginner to advanced level! 🎓

🔥 FREE Learning Resources
🔥 Beginner to Advanced Tutorials
🔥 Practical Examples & Exercises
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🔗 𝗟𝗶𝗻𝗸👇:-

https://pdlink.in/4jDfcCP

⚡ One powerful skill can open doors to multiple career opportunities!

🧠 SQL Concepts You'll Practice

✔ DDL & DML

✔ INNER JOIN

✔ LEFT JOIN

✔ GROUP BY

✔ HAVING

✔ Aggregate Functions

✔ CASE WHEN

✔ CTEs

✔ Window Functions

✔ Date & Time Functions

📊 Business KPIs You Can Build

📈 Total Orders

📈 Total Revenue

📈 Average Order Value (AOV)

📈 Average Delivery Time

📈 On-Time Delivery Rate

📈 Delayed Delivery Rate

📈 Orders by Hour

📈 Peak Ordering Hour

📈 Orders by Day of Week

📈 Revenue by Restaurant

📈 Revenue by City

📈 Top 10 Restaurants

📈 Top Customers by Spending

📈 Average Restaurant Rating

📈 Delivery Partner Performance

📈 Average Orders per Delivery Partner

📈 Highest Revenue Cuisine

📈 Customer Retention Rate

📈 Repeat Order Rate

📈 Cancellation Rate

📈 Delivery Time by City

📈 Delivery Time by Cuisine

📈 Revenue Trend (Daily & Monthly)

📈 Restaurant Market Share

📈 Customer Lifetime Value (CLV)

🎯 This project simulates the SQL work performed by Data Analysts at companies like Swiggy, Zomato, Uber Eats, and DoorDash, making it an excellent portfolio project for analytics interviews.

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🚀 SQL Project Series #8

Food Delivery Analytics 🍔

Analyze customer orders, restaurant performance, delivery efficiency, and rider operations using SQL.

🎯 Business Objectives

✅ Analyze food orders and revenue

✅ Measure delivery performance

✅ Evaluate restaurant performance

✅ Analyze customer ordering behavior

✅ Track delivery partner efficiency

✅ Identify peak order hours

✅ Reduce delivery delays

✅ Improve customer satisfaction

📂 Step 1: Create Database

CREATE DATABASE food_delivery_db;

USE food_delivery_db;

📂 Step 2: Create Customers Table

CREATE TABLE customers (
customer_id INT PRIMARY KEY,
customer_name VARCHAR(100),
city VARCHAR(50),
signup_date DATE
);

📂 Step 3: Create Restaurants Table

CREATE TABLE restaurants (
restaurant_id INT PRIMARY KEY,
restaurant_name VARCHAR(100),
cuisine VARCHAR(50),
city VARCHAR(50),
rating DECIMAL(3,2)
);

📂 Step 4: Create Delivery Partners Table

CREATE TABLE delivery_partners (
partner_id INT PRIMARY KEY,
partner_name VARCHAR(100),
vehicle_type VARCHAR(30)
);

📂 Step 5: Create Orders Table

CREATE TABLE orders (
order_id INT PRIMARY KEY,
customer_id INT,
restaurant_id INT,
partner_id INT,
order_date TIMESTAMP,
delivery_time_minutes INT,
order_amount DECIMAL(10,2),
order_status VARCHAR(20),
FOREIGN KEY (customer_id) REFERENCES customers(customer_id),
FOREIGN KEY (restaurant_id) REFERENCES restaurants(restaurant_id),
FOREIGN KEY (partner_id) REFERENCES delivery_partners(partner_id)
);

📂 Step 6: Insert Sample Customers

INSERT INTO customers VALUES
(1,'Rahul','Mumbai','2025-01-10'),
(2,'Priya','Delhi','2025-01-12'),
(3,'Amit','Pune','2025-01-18'),
(4,'Sneha','Bangalore','2025-01-22'),
(5,'Rohan','Hyderabad','2025-01-25');

📂 Step 7: Insert Sample Restaurants

INSERT INTO restaurants VALUES
(101,'Pizza Hub','Italian','Mumbai',4.6),
(102,'Spice Villa','Indian','Delhi',4.4),
(103,'Burger Point','Fast Food','Pune',4.2),
(104,'Sushi World','Japanese','Bangalore',4.8);

📂 Step 8: Insert Sample Delivery Partners

INSERT INTO delivery_partners VALUES
(201,'Aman','Bike'),
(202,'Rohit','Scooter'),
(203,'Vikas','Bike'),
(204,'Ankit','Bicycle');

📂 Step 9: Insert Sample Orders

INSERT INTO orders VALUES
(1001,1,101,201,'2025-02-01 12:30:00',28,850,'Delivered'),
(1002,2,102,202,'2025-02-01 13:10:00',42,620,'Delivered'),
(1003,3,103,201,'2025-02-01 19:45:00',35,480,'Delivered'),
(1004,4,104,203,'2025-02-02 20:15:00',55,1200,'Delayed'),
(1005,5,101,204,'2025-02-03 18:20:00',25,760,'Delivered');

𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝗰𝗲 & 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗙𝗥𝗘𝗘 𝗢𝗻𝗹𝗶𝗻𝗲 𝗠𝗮𝘀𝘁𝗲𝗿𝗰𝗹𝗮𝘀𝘀 📊

Build a strong foundation in Data Science .Explore Machine Learning and Deep Learning

Eligibility :- Students • Freshers • Working Professionals

📅 Date:- 23 October 2026
⏰ Time:- 7:00 PM–9:00 PM IST
💻 Mode:- Online

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📢 Share this opportunity with your friends and classmates.

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🚀 SQL Project Series #7

Hospital Management Analysis 🏥

Learn how hospitals use SQL to analyze patient data, optimize operations, improve resource utilization, and generate healthcare insights.

🎯 Business Objectives
✅ Analyze patient admissions
✅ Monitor doctor performance
✅ Track appointment trends
✅ Measure bed occupancy
✅ Analyze treatment costs
✅ Identify readmitted patients
✅ Calculate average length of stay
✅ Improve hospital efficiency

📂 Step 1: Create Database

CREATE DATABASE hospital_db;

USE hospital_db;

📂 Step 2: Create Patients Table

CREATE TABLE patients (
patient_id INT PRIMARY KEY,
patient_name VARCHAR(100),
gender VARCHAR(10),
age INT,
city VARCHAR(50),
registration_date DATE
);

📂 Step 3: Create Doctors Table

CREATE TABLE doctors (
doctor_id INT PRIMARY KEY,
doctor_name VARCHAR(100),
specialization VARCHAR(100),
department VARCHAR(100)
);

📂 Step 4: Create Appointments Table

CREATE TABLE appointments (
appointment_id INT PRIMARY KEY,
patient_id INT,
doctor_id INT,
appointment_date DATE,
status VARCHAR(20),
consultation_fee DECIMAL(10,2),
FOREIGN KEY (patient_id) REFERENCES patients(patient_id),
FOREIGN KEY (doctor_id) REFERENCES doctors(doctor_id)
);

📂 Step 5: Create Admissions Table

CREATE TABLE admissions (
admission_id INT PRIMARY KEY,
patient_id INT,
admission_date DATE,
discharge_date DATE,
diagnosis VARCHAR(100),
treatment_cost DECIMAL(12,2),
FOREIGN KEY (patient_id) REFERENCES patients(patient_id)
);

📂 Step 6: Insert Sample Patients

INSERT INTO patients VALUES
(1,'Rahul Sharma','Male',34,'Mumbai','2024-01-05'),
(2,'Priya Verma','Female',29,'Delhi','2024-01-10'),
(3,'Amit Patel','Male',42,'Pune','2024-02-15'),
(4,'Sneha Joshi','Female',37,'Bangalore','2024-03-01'),
(5,'Rohan Gupta','Male',51,'Hyderabad','2024-03-20');

📂 Step 7: Insert Sample Doctors

INSERT INTO doctors VALUES
(101,'Dr. Mehta','Cardiology','Heart Care'),
(102,'Dr. Singh','Orthopedics','Bone Care'),
(103,'Dr. Rao','Neurology','Neuro Care'),
(104,'Dr. Shah','General Medicine','General');

📂 Step 8: Insert Sample Appointments

INSERT INTO appointments VALUES
(1001,1,101,'2025-01-05','Completed',800),
(1002,2,104,'2025-01-06','Completed',500),
(1003,3,102,'2025-01-08','Cancelled',700),
(1004,4,103,'2025-01-09','Completed',1000),
(1005,5,101,'2025-01-12','Completed',800);

📂 Step 9: Insert Sample Admissions

INSERT INTO admissions VALUES
(201,1,'2025-01-05','2025-01-10','Heart Surgery',250000),
(202,2,'2025-01-08','2025-01-11','Fever',12000),
(203,3,'2025-01-15','2025-01-22','Fracture',85000),
(204,5,'2025-01-18','2025-01-21','Cardiac Checkup',45000);

🧠 SQL Concepts You'll Practice
✔ DDL & DML
✔ Joins
✔ Aggregate Functions
✔ GROUP BY
✔ HAVING
✔ CASE WHEN
✔ CTEs
✔ Window Functions
✔ Date Functions
✔ Ranking Functions

📊 Business KPIs You Can Build
📈 Total Patients
📈 Total Admissions
📈 Total Appointments
📈 Appointment Completion Rate
📈 Appointment Cancellation Rate
📈 Doctor-wise Patient Count
📈 Department-wise Revenue
📈 Average Consultation Fee
📈 Average Treatment Cost
📈 Average Length of Stay
📈 Daily Patient Admissions
📈 Monthly Admission Trend
📈 Readmission Rate
📈 Bed Occupancy Rate
📈 Top Doctors by Patient Volume
📈 Revenue by Department
📈 Revenue by Doctor
📈 Most Common Diagnosis
📈 Patient Distribution by City
📈 Average Patient Age

🎯 This project reflects the type of SQL analysis performed by Healthcare Analysts, Hospital Operations teams, Business Intelligence Analysts, and Data Analysts working in hospitals and health-tech companies.

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