Curriculum
SQL Analytics Project is the final lesson of the SQL for Data Analytics section. This project combines all the concepts learned throughout the SQL curriculum, including databases, tables, SQL queries, filtering, sorting, aggregate functions, GROUP BY, HAVING, joins, subqueries, views, stored procedures, and optimization techniques.
In real-world organizations, Data Analysts use SQL to extract insights from large datasets and support business decisions. This SQL Analytics Project simulates a practical business environment where an analyst must answer important business questions using SQL.
By completing this project, learners will gain hands-on experience working with realistic business data and performing analytical tasks commonly used in Data Analytics, Business Intelligence, and Reporting.
Organizations use SQL Analytics Projects to:
The SQL Analytics Project helps bridge the gap between theory and real-world application.
In this project, we will analyze data for an e-commerce company.
The company maintains information about:
The goal is to generate insights that help management improve business performance.
The management team wants answers to questions such as:
These questions are commonly answered using SQL.
The project uses multiple related tables.
Stores customer information.
| Column Name | Data Type |
|---|---|
| CustomerID | INT |
| CustomerName | VARCHAR(100) |
| City | VARCHAR(50) |
| VARCHAR(100) |
Stores product information.
| Column Name | Data Type |
|---|---|
| ProductID | INT |
| ProductName | VARCHAR(100) |
| Category | VARCHAR(50) |
| Price | DECIMAL(10,2) |
Stores order information.
| Column Name | Data Type |
|---|---|
| OrderID | INT |
| CustomerID | INT |
| ProductID | INT |
| Quantity | INT |
| OrderDate | DATE |
CREATE DATABASE ecommerce_analytics;Select the database:
USE ecommerce_analytics;This creates the project environment.
CREATE TABLE Customers (
CustomerID INT PRIMARY KEY,
CustomerName VARCHAR(100),
City VARCHAR(50),
Email VARCHAR(100)
);The table stores customer records.
CREATE TABLE Products (
ProductID INT PRIMARY KEY,
ProductName VARCHAR(100),
Category VARCHAR(50),
Price DECIMAL(10,2)
);The table stores product details.
CREATE TABLE Orders (
OrderID INT PRIMARY KEY,
CustomerID INT,
ProductID INT,
Quantity INT,
OrderDate DATE
);The table stores transaction records.
INSERT INTO Customers VALUES
(101,'Rahul Sharma','Jaipur','rahul@email.com'),
(102,'Priya Verma','Delhi','priya@email.com'),
(103,'Amit Kumar','Mumbai','amit@email.com');The project now contains customer records.
INSERT INTO Products VALUES
(1,'Laptop','Electronics',50000),
(2,'Mobile','Electronics',25000),
(3,'Office Chair','Furniture',10000);The project now contains product information.
INSERT INTO Orders VALUES
(1001,101,1,1,'2026-01-15'),
(1002,102,2,2,'2026-01-18'),
(1003,101,3,1,'2026-02-10');The project now contains sales transactions.
Business Requirement:
View all customers.
Query:
SELECT *
FROM Customers;Applications:
Customer reporting.
Business Requirement:
Determine customer base size.
Query:
SELECT COUNT(*) AS TotalCustomers
FROM Customers;Applications:
Customer analytics.
Business Requirement:
Calculate total business revenue.
Query:
SELECT SUM(P.Price * O.Quantity) AS TotalRevenue
FROM Orders O
INNER JOIN Products P
ON O.ProductID = P.ProductID;Applications:
Financial reporting.
Business Requirement:
Identify top-performing products.
Query:
SELECT ProductName,
Price
FROM Products
WHERE Price =
(
SELECT MAX(Price)
FROM Products
);Applications:
Product analysis.
Business Requirement:
Analyze category performance.
Query:
SELECT Category,
SUM(Price) AS Revenue
FROM Products
GROUP BY Category;Applications:
Sales analytics.
Business Requirement:
View customer purchases.
Query:
SELECT C.CustomerName,
O.OrderID
FROM Customers C
INNER JOIN Orders O
ON C.CustomerID = O.CustomerID;Applications:
Customer behavior analysis.
Business Requirement:
Understand geographic distribution.
Query:
SELECT City,
COUNT(*) AS CustomerCount
FROM Customers
GROUP BY City;Applications:
Regional reporting.
Business Requirement:
Analyze sales trends.
Query:
SELECT MONTH(OrderDate) AS SalesMonth,
COUNT(*) AS TotalOrders
FROM Orders
GROUP BY MONTH(OrderDate);Applications:
Trend analysis.
Business Requirement:
Identify underperforming products.
Query:
SELECT ProductName
FROM Products
WHERE ProductID NOT IN
(
SELECT ProductID
FROM Orders
);Applications:
Inventory optimization.
Business Requirement:
Create reusable reporting logic.
Query:
CREATE VIEW SalesSummary AS
SELECT C.CustomerName,
P.ProductName,
O.Quantity
FROM Orders O
INNER JOIN Customers C
ON O.CustomerID = C.CustomerID
INNER JOIN Products P
ON O.ProductID = P.ProductID;Applications:
Dashboard development.
Business Requirement:
Automate reporting.
Query:
CREATE PROCEDURE GetRevenue()
BEGIN
SELECT SUM(P.Price * O.Quantity)
FROM Orders O
INNER JOIN Products P
ON O.ProductID = P.ProductID;
END;Execution:
CALL GetRevenue();Applications:
Executive reporting.
Business Requirement:
Improve query speed.
Create Index:
CREATE INDEX idx_customer
ON Customers(CustomerID);Benefits:
Data Analysts frequently prepare datasets for:
Example:
SELECT C.City,
SUM(P.Price * O.Quantity) AS Revenue
FROM Orders O
INNER JOIN Customers C
ON O.CustomerID = C.CustomerID
INNER JOIN Products P
ON O.ProductID = P.ProductID
GROUP BY C.City;This dataset can be used directly in dashboards.
This project demonstrates how SQL supports:
These skills are essential for modern Data Analysts.
Business Intelligence professionals use similar projects to:
The SQL Analytics Project closely resembles real-world business scenarios.
Throughout this project, learners applied:
This project integrates all major SQL concepts.
Industries that use SQL Analytics Projects include:
Customer and sales analysis.
Transaction analysis.
Patient reporting.
Student analytics.
Production reporting.
Inventory and revenue analysis.
SQL is used across nearly every industry.
Focus on business goals.
Improve maintainability.
Improve performance.
Ensure accuracy.
Improve collaboration.
Use Views and Stored Procedures.
These practices support professional Data Analytics workflows.
After completing this lesson, you will be able to:
A SQL Analytics Project is a practical business case that uses SQL to analyze and report data.
It helps learners apply SQL concepts in real-world scenarios.
Databases, tables, joins, aggregate functions, subqueries, views, stored procedures, and optimization techniques.
Yes. The generated datasets can be used in Power BI dashboards.
Yes. It combines beginner and intermediate SQL concepts.
E-commerce, banking, healthcare, education, manufacturing, and retail.
Joins combine related data from multiple tables.
It provides practical experience solving business problems using SQL.
Want to master SQL, reporting, and Data Analytics?