SQL for Data Analytics

A practical SQL repository by YBI Foundation containing SQL queries, databases, datasets, and end-to-end analytics projects designed for learning and practicing SQL for Data Analysis.

This repository covers SQL fundamentals through advanced analytics concepts using real-world business scenarios such as Marketing Analytics, Retail Sales, and Supply Chain Analytics.

📚 What's Inside

Project / Dataset	Description
Digital Marketing Analytics	SQL queries for analyzing digital marketing performance
Marketing Analytics	Marketing dataset and SQL database for analytics practice
Marketing Joins	Database designed for practicing SQL JOIN operations
QueryMart – Retail Sales	Retail sales database with customers, products, orders, items, and warehouses
Supply Chain Analytics	Supply chain dataset for business and operational analysis
Supply Chain Advanced Analytics	Advanced supply chain analytics dataset

🛒 QueryMart – Retail Sales Analytics

QueryMart is a retail business database designed for practicing SQL in a realistic business environment.

The project contains multiple related tables covering:

Customers
Products
Orders
Items
Warehouses

Database Files

Example Business Questions

Using the QueryMart database, learners can answer questions such as:

What is the total revenue?
What are the top-selling products?
Which customers generate the highest revenue?
What is the average order value?
Which warehouses generate the most revenue?
What are the monthly sales trends?
What are the most expensive orders?
Which products have the highest sales?
How does revenue vary by warehouse?
What is the running total of revenue?
What is the rank of each warehouse by revenue?

📣 Digital Marketing Analytics

The Digital Marketing Analytics project contains SQL queries for analyzing marketing performance.

File

DigitalMarketingAnalytics.sql

The project can be used to practice:

Marketing campaign analysis
Customer acquisition analysis
Conversion analysis
Revenue analysis
Campaign performance
Channel performance
Aggregations
Filtering
Grouping
Subqueries
CASE statements
Window functions

📊 Marketing Analytics

The Marketing Analytics database provides a structured dataset for practicing SQL-based business analysis.

Files

SQL Concepts

This project can be used to practice:

SELECT
WHERE
ORDER BY
GROUP BY
HAVING
Aggregate Functions
CASE
String Functions
Date Functions
Subqueries
JOIN
Window Functions
Business KPIs

🔗 SQL JOIN Practice

MarketingJoin.db is designed specifically for understanding and practicing SQL joins.

Topics include:

INNER JOIN
LEFT JOIN
RIGHT JOIN
FULL OUTER JOIN
SELF JOIN
CROSS JOIN

The database can be used to understand how multiple business tables are connected and how data can be combined for analysis.

🚚 Supply Chain Analytics

The repository also contains supply chain datasets for analyzing operational and business performance.

Supply Chain Analytics

Advanced Supply Chain Analytics

These datasets can be used to practice analysis around:

Inventory
Orders
Suppliers
Products
Warehouses
Logistics
Delivery performance
Supply chain efficiency
Operational KPIs
Business performance

🧠 SQL Learning Roadmap

This repository can be followed progressively:

Level 1 – SQL Fundamentals

SELECT
WHERE
DISTINCT
ORDER BY
LIMIT
Aliases

Level 2 – SQL Functions

Aggregate Functions
String Functions
Date Functions
Mathematical Functions
CASE Statements

Level 3 – Data Aggregation

GROUP BY
HAVING
COUNT
SUM
AVG
MIN
MAX

Level 4 – SQL JOINs

INNER JOIN
LEFT JOIN
RIGHT JOIN
FULL OUTER JOIN
SELF JOIN
CROSS JOIN

Level 5 – Advanced SQL

Subqueries
CTEs
Window Functions
RANK()
DENSE_RANK()
ROW_NUMBER()
LAG()
LEAD()
Running Totals

Level 6 – Business Analytics

Revenue Analysis
Customer Analysis
Product Analysis
Marketing Analytics
Supply Chain Analytics
Sales Analytics
Performance Analysis
KPI Analysis

💻 Working With the Databases

The .db files are SQLite databases and can be opened using:

Python
Jupyter Notebook
Google Colab
SQLite
DB Browser for SQLite
VS Code with SQLite extensions

Example: Using SQLite with Python

import sqlite3
import pandas as pd

conn = sqlite3.connect("QueryMart.db")

query = """
SELECT *
FROM Customers
LIMIT 10;
"""

df = pd.read_sql_query(query, conn)

df

🐍 SQL + Python

These databases can also be used with Python for complete data analytics workflows:

SQLite Database
       ↓
     SQL
       ↓
Data Extraction
       ↓
    Pandas
       ↓
Data Analysis
       ↓
Visualization
       ↓
Business Insights

This makes the repository useful for learners building skills in both SQL and Python Data Analytics.

🎯 Learning Objectives

After working through these projects, learners should be able to:

Write SQL queries confidently
Filter and transform data
Aggregate business data
Combine multiple tables using JOINs
Work with dates and strings
Use conditional logic with CASE
Write subqueries and CTEs
Use window functions
Calculate business KPIs
Analyze sales and marketing data
Perform customer and product analysis
Analyze supply chain performance
Solve real-world business questions using SQL

🏆 Recommended Practice Workflow

For each dataset, follow this workflow:

1. Understand the Business Problem
            ↓
2. Explore the Tables
            ↓
3. Identify Required Columns
            ↓
4. Write SQL Query
            ↓
5. Validate the Result
            ↓
6. Extract Business Insight
            ↓
7. Build Dashboard / Visualization

📁 Repository Structure

SQL/
│
├── DigitalMarketingAnalytics.sql
│
├── MarketingAnalytics.db
├── MarketingJoin.db
│
├── QueryMart.db
├── QueryMartCustomers.csv
├── QueryMartItems.csv
├── QueryMartOrders.csv
├── QueryMartProducts.csv
├── QueryMartWarehouses.csv
│
├── SupplyChainAnalytics.csv
├── SupplyChainAnalytics.db
│
├── SupplyChainAdvanceAnalytics.csv
├── SupplyChainAdvanceAnalytics.db
│
└── README.md

👨‍💻 Who Is This Repository For?

This repository is suitable for:

SQL Beginners
Data Analyst Students
Business Analytics Students
College Students
SQL Interview Preparation
Data Analytics Portfolio Projects
Python + SQL Learners
Aspiring Data Analysts
Professionals refreshing their SQL skills

🚀 How to Use This Repository

Step 1 – Clone the Repository

git clone https://github.com/YBIFoundation/SQL.git

Step 2 – Open the Database

Choose any .db file and open it using SQLite, Python, Jupyter Notebook, Google Colab, or DB Browser for SQLite.

Step 3 – Explore the Tables

Understand the structure, columns, relationships, and available data.

Step 4 – Solve Business Problems

Write SQL queries to answer analytical questions.

Step 5 – Build Your Portfolio

Use the datasets to create:

SQL projects
Data analysis reports
Power BI dashboards
Python analytics projects
GitHub portfolio projects

📌 Projects Included

Project	Format	Focus
Digital Marketing Analytics	`.sql`	Marketing
Marketing Analytics	`.db`	Business Analytics
Marketing Join Practice	`.db`	SQL JOINs
QueryMart Retail Analytics	`.db` + `.csv`	Retail Sales
Supply Chain Analytics	`.db` + `.csv`	Supply Chain
Supply Chain Advanced Analytics	`.db` + `.csv`	Advanced Analytics

⭐ Support the Repository

If you find this repository useful for learning SQL:

⭐ Star this repository

🍴 Fork the repository

📢 Share it with other learners

💻 Build your own project using the datasets

🌐 YBI Foundation

This repository is part of the practical learning resources developed by YBI Foundation for students and aspiring data professionals.

Learn. Practice. Build. Deploy.

YBI Foundation

📜 License

This repository is intended for educational and learning purposes.

Please refer to the repository and individual dataset files for any applicable usage restrictions.

Name		Name	Last commit message	Last commit date
Latest commit History 15 Commits
DigitalMarketingAnalytics.sql		DigitalMarketingAnalytics.sql
MarketingAnalytics.db		MarketingAnalytics.db
MarketingJoin.db		MarketingJoin.db
QueryMart.db		QueryMart.db
QueryMartCustomers.csv		QueryMartCustomers.csv
QueryMartItems.csv		QueryMartItems.csv
QueryMartOrders.csv		QueryMartOrders.csv
QueryMartProducts.csv		QueryMartProducts.csv
QueryMartWarehouses.csv		QueryMartWarehouses.csv
README.md		README.md
SupplyChainAdvanceAnalytics.csv		SupplyChainAdvanceAnalytics.csv
SupplyChainAdvanceAnalytics.db		SupplyChainAdvanceAnalytics.db
SupplyChainAnalytics.csv		SupplyChainAnalytics.csv
SupplyChainAnalytics.db		SupplyChainAnalytics.db

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