Data Analytics Projects - SQL, Excel, Tableau, Python & Power BI Interview Resources
Открыть в Telegram
Covering all technical and popular stuff about anything related to Data Science: AI, Big Data, Machine Learning, Statistics, general Math and the applications of former. Ads/ Promo: @love_data
Больше
Сеть:📈 Аналитический обзор Telegram-канала Data Analytics Projects - SQL, Excel, Tableau, Python & Power BI Interview Resources
Канал Data Analytics Projects - SQL, Excel, Tableau, Python & Power BI Interview Resources (@sqlproject) языкового сегмента Английский является активным участником. Сейчас сообщество объединяет 39 615 подписчиков, занимая 4 706 место в категории Образование и 9 734 место в регионе Индия.
📊 Показатели аудитории и динамика
С момента создания невідомо проект демонстрирует стремительный рост, собрав аудиторию из 39 615 подписчиков.
Согласно последним данным от 25 октября, 2026, канал показывает стабильную активность. За последние 30 дней изменение числа участников составило -62, а за последние 24 часа — -6, при этом общий охват остаётся высоким.
- Статус верификации: Не верифицирован
- Уровень вовлечённости (ER): Средний показатель вовлечённости аудитории составляет 2.30%. В первые 24 часа после публикации контент обычно набирает 0.70% реакций от общего числа подписчиков.
- Охват публикаций: В среднем каждый пост получает 911 просмотров. В течение первых суток публикация набирает 277 просмотров.
- Реакции и взаимодействия: Аудитория активно поддерживает контент: среднее количество реакций на один пост — 3.
- Тематические интересы: Контент сосредоточен на ключевых темах, таких как analytic, dataset, visualization, sql, learning.
📝 Описание и контентная политика
Автор описывает ресурс как площадку для выражения субъективного мнения:
“Covering all technical and popular stuff about anything related to Data Science: AI, Big Data, Machine Learning, Statistics, general Math and the applications of former.
Ads/ Promo: @love_data”
Благодаря высокой частоте обновлений (последние данные получены 26 октября, 2026) канал поддерживает актуальность и высокий уровень охвата публикаций. Аналитика показывает, что аудитория активно взаимодействует с контентом, что делает его важной точкой влияния в категории Образование.
39 615
Подписчики
-624 часа
-667 дней
-6230 дней
Загружаем данные
Похожие каналы
Облако тегов
Входящие и исходящие упоминания
---
---
---
---
---
---
Привлечение подписчиков
октябрь '26окт. '26
октябрь '26
+120
в 0 каналах
сентябрь '26
+123
в 1 каналах
Get PRO
август '26
+254
в 0 каналах
Get PRO
июль '26
+264
в 1 каналах
Get PRO
июнь '26
+246
в 0 каналах
Get PRO
май '26
+379
в 0 каналах
Get PRO
апрель '26
+257
в 1 каналах
Get PRO
март '26
+245
в 0 каналах
Get PRO
февраль '26
+427
в 0 каналах
Get PRO
январь '26
+666
в 4 каналах
Get PRO
декабрь '25
+605
в 1 каналах
Get PRO
ноябрь '25
+671
в 0 каналах
Get PRO
октябрь '25
+565
в 3 каналах
Get PRO
сентябрь '25
+460
в 1 каналах
Get PRO
август '25
+526
в 0 каналах
Get PRO
июль '25
+658
в 5 каналах
Get PRO
июнь '25
+1 062
в 0 каналах
Get PRO
май '25
+2 166
в 2 каналах
Get PRO
апрель '25
+3 376
в 3 каналах
Get PRO
март '25
+1 113
в 7 каналах
Get PRO
февраль '25
+742
в 7 каналах
Get PRO
январь '25
+1 164
в 6 каналах
Get PRO
декабрь '24
+798
в 2 каналах
Get PRO
ноябрь '24
+1 299
в 9 каналах
Get PRO
октябрь '24
+1 702
в 6 каналах
Get PRO
сентябрь '24
+3 195
в 7 каналах
Get PRO
август '24
+4 034
в 4 каналах
Get PRO
июль '24
+2 706
в 10 каналах
Get PRO
июнь '24
+3 039
в 3 каналах
Get PRO
май '24
+2 027
в 1 каналах
Get PRO
апрель '24
+1 994
в 0 каналах
Get PRO
март '24
+2 365
в 2 каналах
Get PRO
февраль '24
+1 487
в 0 каналах
Get PRO
январь '24
+1 412
в 1 каналах
Get PRO
декабрь '23
+1 560
в 3 каналах
| Дата | Привлечение подписчиков | Упоминания | Каналы | |
| 26 октября | +3 | |||
| 25 октября | +4 | |||
| 24 октября | 0 | |||
| 23 октября | 0 | |||
| 22 октября | +4 | |||
| 21 октября | 0 | |||
| 20 октября | +3 | |||
| 19 октября | +1 | |||
| 18 октября | +2 | |||
| 17 октября | +4 | |||
| 16 октября | +5 | |||
| 15 октября | +1 | |||
| 14 октября | +7 | |||
| 13 октября | +6 | |||
| 12 октября | 0 | |||
| 11 октября | 0 | |||
| 10 октября | +3 | |||
| 09 октября | +6 | |||
| 08 октября | 0 | |||
| 07 октября | +9 | |||
| 06 октября | +19 | |||
| 05 октября | +6 | |||
| 04 октября | +18 | |||
| 03 октября | +8 | |||
| 02 октября | +11 | |||
| 01 октября | 0 |
Посты канала
🚀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
🔥 Learn Anytime, Anywhere
🔗 𝗟𝗶𝗻𝗸👇:-
https://pdlink.in/4jDfcCP
⚡ One powerful skill can open doors to multiple career opportunities!
| 2 | 🧠 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.
💡 Double Tap ❤️ For More | 427 |
| 3 | 🚀 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'); | 350 |
| 4 |  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
🔗 𝗥𝗲𝗴𝗶𝘀𝘁𝗲𝗿 𝗙𝗼𝗿 𝗙𝗥𝗘𝗘👇 :-
https://pdlink.in/4i8MKGn
📢 Share this opportunity with your friends and classmates. | 484 |
| 5 |  𝗠𝗜𝗖𝗥𝗢𝗦𝗢𝗙𝗧 𝗙𝗥𝗘𝗘 𝗗𝗔𝗧𝗔 𝗦𝗖𝗜𝗘𝗡𝗖𝗘 𝗥𝗘𝗦𝗢𝗨𝗥𝗖𝗘𝗦 𝟮𝟬𝟮𝟲! 🎓
Microsoft offers valuable FREE learning resources to help you develop in-demand technical skills! 💻
✅ 100% FREE Learning Resources
✅ Beginner-Friendly Tutorials
✅ Self-Paced Learning
✅ Practical Skills for Real-World Projects
✅ Useful for Data Analytics & Data Science Career Preparation
🔗 𝗔𝗰𝗰𝗲𝘀𝘀 𝗔𝗟𝗟 𝟰 𝗙𝗥𝗘𝗘 𝗥𝗲𝘀𝗼𝘂𝗿𝗰𝗲𝘀 👇:-
https://pdlink.in/4k6ylNq
⚡ Your Data Science journey can start today — completely FREE! | 577 |
| 6 | Pandas in 8 Pages.pdf | 693 |
| 7 | 🚀 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.
💡 Double Tap ❤️ For More | 755 |
| 8 |  𝗧𝗔𝗧𝗔 𝗙𝗥𝗘𝗘 𝗠𝗜𝗖𝗥𝗢-𝗜𝗡𝗧𝗘𝗥𝗡𝗦𝗛𝗜𝗣𝗦 𝟮𝟬𝟮𝟲! 🎓
✅ 100% FREE Learning Experience
✅ Short Programs — Approximately 4–6 Hours
✅ Practical, Real-World Tasks
✅ Self-Paced & Online
✅ Certificate Opportunities for Your Resume & LinkedIn
✅ No Traditional Interview Process
🔗 𝗘𝘅𝗽𝗹𝗼𝗿𝗲 𝗧𝗔𝗧𝗔 𝗙𝗥𝗘𝗘 𝗠𝗶𝗰𝗿𝗼-𝗜𝗻𝘁𝗲𝗿𝗻𝘀𝗵𝗶𝗽𝘀👇:-
https://pdlink.in/4yWgaPn
⚡ Don't wait for your first job to start gaining practical experience! | 612 |
| 9 |  𝟰 𝗙𝗥𝗘𝗘 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝗧𝗼 𝗠𝗮𝘀𝘁𝗲𝗿 𝗖𝗼𝗱𝗶𝗻𝗴 𝗙𝗼𝗿 𝗙𝗥𝗘𝗘😍
✅ 100% FREE YouTube Learning
✅ Beginner-Friendly Programming Tutorials
✅ Learn Popular & In-Demand Tech Skills
✅ Study at Your Own Pace
✅ Build a Strong Foundation for Coding Interviews
🔗 𝗔𝗰𝗰𝗲𝘀𝘀 𝗔𝗟𝗟 𝟰 𝗙𝗥𝗘𝗘 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 👇:-
https://pdlink.in/3WcuMvi
⚡ Your coding journey can start today—completely FREE! | 697 |
| 10 |  𝗜𝗕𝗠 𝗙𝗥𝗘𝗘 𝗧𝗘𝗖𝗛 𝗖𝗢𝗨𝗥𝗦𝗘𝗦 𝟮𝟬𝟮𝟲! 🎓
Explore IBM Cognitive Class and build in-demand tech skills without spending money on course fees!
📚 𝗧𝗼𝗽 𝗙𝗥𝗘𝗘 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝘁𝗼 𝗘𝘅𝗽𝗹𝗼𝗿𝗲:-
💫 Artificial Intelligence & Machine Learning
🔥Python for Data Science
📊 Data Science Fundamentals
☁️ Cloud Computing & Big Data
🔗 𝗦𝘁𝗮𝗿𝘁 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗛𝗲𝗿𝗲 👇
https://pdlink.in/4zGswuX
📲 Save & Share with friends preparing for tech careers! 🔥 | 794 |
| 11 |  𝗗𝗮𝘁𝗮 𝘀𝗰𝗶𝗲𝗻𝗰𝗲 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗪𝗶𝘁𝗵 𝗔𝗜😍
Future Ready Data Science and AI Skills You Build
->Build Python, Machine Learning, and AI Skills
->Get Mentored by Industry Experts
->Practice with Mock Interviews
->Ace Your Placements & Land Dream Tech Job
🤝 500+ Partner Companies |🎓 2000+ Students Placed
🔗 𝗥𝗲𝗴𝗶𝘀𝘁𝗲𝗿 𝗡𝗼𝘄 👇 :-
https://pdlink.in/47pezFz
📲 Save & Share with Friends Preparing for Data Science & AI Jobs! | 769 |
| 12 |  𝗧𝗢𝗣 𝗙𝗥𝗘𝗘 𝗖𝗢𝗨𝗥𝗦𝗘𝗦 𝗧𝗢 𝗕𝗢𝗢𝗦𝗧 𝗬𝗢𝗨𝗥 𝗦𝗞𝗜𝗟𝗟𝗦 𝗜𝗡 𝟮𝟬𝟮𝟲!
Explore FREE online learning resources to develop in-demand skills and improve your career opportunities!
🎓 Why Explore These Courses?
✅ Learn valuable professional skills
✅ Improve your resume
✅ Build practical knowledge
✅ Learn at your own pace
𝗘𝘅𝗽𝗹𝗼𝗿𝗲 𝗙𝗥𝗘𝗘 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝗛𝗲𝗿𝗲👇
https://pdlink.in/3VBdt6V
💡 Learn New Skills → Build Confidence → Unlock Career Opportunities! | 1 062 |
| 13 |  🚀 𝗪𝗵𝗶𝗰𝗵 𝗧𝗲𝗰𝗵 𝗦𝗸𝗶𝗹𝗹 𝗪𝗶𝗹𝗹 𝗬𝗼𝘂 𝗠𝗮𝘀𝘁𝗲𝗿 𝗶𝗻 𝟮𝟬𝟮𝟲?
Want to build apps, uncover insights, or create AI solutions? Explore certification courses that match your career goals! 🎯
💻 𝗙𝘂𝗹𝗹 𝗦𝘁𝗮𝗰𝗸 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁
👉 https://pdlink.in/3SuUeuD
📊 𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀
👉 https://pdlink.in/45vk5ph
💫𝗔𝗜 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴
👉 https://pdlink.in/4fWJVID
🔥 Choose your path, sharpen your skills, and take the next step towards your tech career!
📌 Save this post & share it with a friend planning to upskill. | 1 008 |
| 14 | 🚀 SQL Project Series #6: Banking Transaction Analysis 🏦
Learn how banks use SQL to analyze customer transactions, monitor account activity, detect fraud, and generate business insights.
🎯 Business Objectives
✅ Analyze customer transactions
✅ Calculate account balances
✅ Identify high-value customers
✅ Detect suspicious transactions
✅ Monitor transaction trends
✅ Analyze deposits vs withdrawals
✅ Measure customer activity
✅ Identify dormant accounts
✅ Generate banking KPIs
📂 Step 1: Create Database
CREATE DATABASE banking_db;
USE banking_db;
📂 Step 2: Create Customers Table
CREATE TABLE customers (
customer_id INT PRIMARY KEY,
customer_name VARCHAR(100),
gender VARCHAR(10),
city VARCHAR(50),
account_open_date DATE
);
📂 Step 3: Create Accounts Table
CREATE TABLE accounts (
account_id INT PRIMARY KEY,
customer_id INT,
account_type VARCHAR(30),
branch_name VARCHAR(100),
opening_balance DECIMAL(12,2),
FOREIGN KEY (customer_id)
REFERENCES customers(customer_id)
);
📂 Step 4: Create Transactions Table
CREATE TABLE transactions (
transaction_id INT PRIMARY KEY,
account_id INT,
transaction_date TIMESTAMP,
transaction_type VARCHAR(20),
amount DECIMAL(12,2),
FOREIGN KEY (account_id)
REFERENCES accounts(account_id)
);
📂 Step 5: Insert Sample Customers
INSERT INTO customers VALUES
(1,'Rahul Sharma','Male','Mumbai','2023-01-10'),
(2,'Priya Verma','Female','Delhi','2023-02-18'),
(3,'Amit Patel','Male','Pune','2023-04-12'),
(4,'Sneha Joshi','Female','Bangalore','2023-05-22'),
(5,'Rohan Gupta','Male','Hyderabad','2023-08-01');
📂 Step 6: Insert Sample Accounts
INSERT INTO accounts VALUES
(101,1,'Savings','Mumbai',50000),
(102,2,'Savings','Delhi',35000),
(103,3,'Current','Pune',100000),
(104,4,'Savings','Bangalore',45000),
(105,5,'Current','Hyderabad',75000);
📂 Step 7: Insert Sample Transactions
INSERT INTO transactions VALUES
(1001,101,'2025-01-05 10:15:00','Deposit',15000),
(1002,101,'2025-01-06 12:30:00','Withdrawal',5000),
(1003,102,'2025-01-07 14:20:00','Deposit',25000),
(1004,103,'2025-01-08 16:10:00','Withdrawal',30000),
(1005,104,'2025-01-09 09:45:00','Deposit',12000),
(1006,105,'2025-01-10 11:00:00','Withdrawal',10000);
🧠 SQL Concepts You'll Practice
✔ DDL Commands
✔ DML Commands
✔ Primary & Foreign Keys
✔ Joins
✔ Aggregate Functions
✔ CASE WHEN
✔ GROUP BY
✔ HAVING
✔ Window Functions
✔ CTEs
✔ Date & Time Functions
📊 Business KPIs You Can Build
📈 Total Transaction Amount
📈 Total Deposits
📈 Total Withdrawals
📈 Net Cash Flow
📈 Current Account Balance
📈 Average Transaction Amount
📈 Daily Transaction Volume
📈 Monthly Transaction Trend
📈 Branch-wise Transactions
📈 Account Type Analysis
📈 Top Customers by Transaction Value
📈 Most Active Customers
📈 Dormant Accounts
📈 High-Value Transactions
📈 Deposit vs Withdrawal Ratio
📈 Fraud Detection Alerts
📈 Average Balance by Branch
📈 Customer Growth
📈 Transaction Success Rate
📈 Peak Transaction Hours
💡 Double Tap ❤️ For More | 1 032 |
| 15 |  🇮🇳 𝗚𝗢𝗩𝗘𝗥𝗡𝗠𝗘𝗡𝗧 𝗢𝗙 𝗜𝗡𝗗𝗜𝗔 — 𝗔𝗜𝗖𝗧𝗘 𝗜𝗡𝗧𝗘𝗥𝗡𝗦𝗛𝗜𝗣𝗦 𝟮𝟬𝟮𝟲 🚀
Students and freshers can explore internship opportunities through the AICTE Internship Portal across multiple domains:
💻 AI, Data Science & Web Development
📈 Digital Marketing & Business Development
💰 Finance & Accounting
✍️ Content Writing & Graphic Design
⚙️ Mechanical, Civil & Electrical Engineering
🔗 𝗖𝗵𝗲𝗰𝗸 𝗢𝗽𝗽𝗼𝗿𝘁𝘂𝗻𝗶𝘁𝗶𝗲𝘀 & 𝗔𝗽𝗽𝗹𝘆 👇
https://pdlink.in/4y3vcBl
📢 Share this opportunity with your friends and classmates! | 850 |
| 16 |  🎓 𝗠𝗶𝗰𝗿𝗼𝘀𝗼𝗳𝘁 𝗙𝗥𝗘𝗘 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝘄𝗶𝘁𝗵 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗲𝘀! 🚀🔥
Upgrade your resume with Microsoft learning opportunities. Explore courses covering some of today's most in-demand tech skills!
🎯 Perfect for Students • Freshers • Job Seekers • Working Professionals
✅ Learn at your own pace ✅ Build career-relevant skills ✅ Explore available certificates and credentials
🔗 𝗔𝗰𝗰𝗲𝘀𝘀 𝗠𝗶𝗰𝗿𝗼𝘀𝗼𝗳𝘁 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝗛𝗲𝗿𝗲 👇
https://pdlink.in/3Uf5trR
🔥 Share with friends looking to upskill in 2026! | 946 |
| 17 |  🚀𝗣𝗮𝘆 𝗔𝗳𝘁𝗲𝗿 𝗣𝗹𝗮𝗰𝗲𝗺𝗲𝗻𝘁 𝗧𝗿𝗮𝗶𝗻𝗶𝗻𝗴 | 𝗕𝗲𝗰𝗼𝗺𝗲 𝗮 𝗙𝘂𝗹𝗹𝘀𝘁𝗮𝗰𝗸 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗲𝗿 𝗪𝗜𝘁𝗵 𝗚𝗲𝗻𝗔𝗜
Start a high-paying tech career—even without prior coding experience
🏆 𝗣𝗹𝗮𝗰𝗲𝗺𝗲𝗻𝘁 𝗛𝗶𝗴𝗵𝗹𝗶𝗴𝗵𝘁𝘀:
💰 ₹41 LPA highest salary
📈 ₹7.4 LPA average salary
🎓 2,000+ students placed
🏢 500+ hiring partners
✅ 100% job assistance
📜 Skill India–authenticated certificate
🔗 𝗔𝗽𝗽𝗹𝘆 𝗡𝗼𝘄👇:-
https://pdlink.in/3SuUeuD
🎯 HurryUp.....Limited Seats Available | 903 |
| 18 |  𝗠𝗮𝘀𝘁𝗲𝗿 𝗣𝗼𝘄𝗲𝗿 𝗕𝗜 𝗳𝗼𝗿 𝗙𝗥𝗘𝗘! 🔥
Learn Power BI through these FREE learning resources
✨ What You'll Learn:
📊 Interactive Dashboards
📈 Data Visualization
🧹 Data Transformation
💼 Real-World Reporting Skills
🎯 Beginner-Friendly — No Coding Required
𝗦𝘁𝗮𝗿𝘁 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗳𝗼𝗿 𝗙𝗥𝗘𝗘
https://pdlink.in/4hznwlu
💫Perfect for Students • Freshers • Data Analyst Aspirants • Working Professionals | 971 |
| 19 | 📊 Essential SQL Concepts Every Data Analyst Must Know
🚀 SQL is the most important skill for Data Analysts. Almost every analytics job requires working with databases to extract, filter, analyze, and summarize data.
Understanding the following SQL concepts will help you write efficient queries and solve real business problems with data.
1️⃣ SELECT Statement (Data Retrieval)
What it is: Retrieves data from a table.
SELECT name, salary
FROM employees;
Use cases: Retrieving specific columns, viewing datasets, extracting required information.
2️⃣ WHERE Clause (Filtering Data)
What it is: Filters rows based on specific conditions.
SELECT *
FROM orders
WHERE order_amount > 500;
Common conditions: =, >, <, >=, <=, BETWEEN, IN, LIKE
3️⃣ ORDER BY (Sorting Data)
What it is: Sorts query results in ascending or descending order.
SELECT name, salary
FROM employees
ORDER BY salary DESC;
Sorting options: ASC (default), DESC
4️⃣ GROUP BY (Aggregation)
What it is: Groups rows with same values into summary rows.
SELECT department, COUNT(*)
FROM employees
GROUP BY department;
Use cases: Sales per region, customers per country, orders per product category.
5️⃣ Aggregate Functions
What they do: Perform calculations on multiple rows.
SELECT AVG(salary)
FROM employees;
Common functions: COUNT(), SUM(), AVG(), MIN(), MAX()
6️⃣ HAVING Clause
What it is: Filters grouped data after aggregation.
SELECT department, COUNT(*)
FROM employees
GROUP BY department
HAVING COUNT(*) > 5;
Key difference: WHERE filters rows before grouping, HAVING filters groups after aggregation.
7️⃣ SQL JOINS (Combining Tables)
What they do: Combine tables.
-- INNER JOIN
SELECT orders.order_id, customers.customer_name
FROM orders
INNER JOIN customers
ON orders.customer_id = customers.customer_id;
-- LEFT JOIN
SELECT customers.customer_name, orders.order_id
FROM customers
LEFT JOIN orders
ON customers.customer_id = orders.customer_id;
Common types: INNER JOIN, LEFT JOIN, RIGHT JOIN, FULL JOIN
8️⃣ Subqueries
What it is: Query inside another query.
SELECT name
FROM employees
WHERE salary > (SELECT AVG(salary) FROM employees);
Use cases: Comparing values, filtering based on aggregated results.
9️⃣ Common Table Expressions (CTE)
What it is: Temporary result set used inside a query.
WITH high_salary AS (
SELECT name, salary
FROM employees
WHERE salary > 70000
)
SELECT *
FROM high_salary;
Benefits: Cleaner queries, easier debugging, better readability.
🔟 Window Functions
What they do: Perform calculations across rows related to current row.
SELECT name, salary, RANK() OVER (ORDER BY salary DESC) AS salary_rank
FROM employees;
Common functions: ROW_NUMBER(), RANK(), DENSE_RANK(), LAG(), LEAD()
Why SQL is Critical for Data Analysts
• Extract data from databases
• Analyze large datasets efficiently
• Generate reports and dashboards
• Support business decision-making
SQL Resources: https://whatsapp.com/channel/0029VanC5rODzgT6TiTGoa1v
Double Tap ♥️ For More | 1 489 |
| 20 |  𝗙𝗥𝗘𝗘 𝗥𝗲𝘀𝗼𝘂𝗿𝗰𝗲𝘀 𝗧𝗼 𝗟𝗲𝗮𝗿𝗻 𝗔𝗜 𝗶𝗻 𝟮𝟬𝟮𝟲🚀
Explore 6 free resources covering AI fundamentals, tools, deep learning, research and real-world applications.
✅ 100% Free Learning
✅ Beginner-Friendly
✅ AI • ML • Deep Learning
✅ Real-World Applications
🔗 𝗘𝘅𝗽𝗹𝗼𝗿𝗲 𝗙𝗥𝗘𝗘 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 👇
https://pdlink.in/4AFHq5R
📢 Share this valuable opportunity with your friends and classmates! | 1 094 |
