This repository showcases a collection of SQL projects, demonstrating practical implementation of data analysis, database design, and advanced querying techniques. Each project highlights different aspects of SQL, from basic data retrieval to complex analytical queries solving real-world business problems.
A comprehensive SQL-based analysis of Walmart's multi-branch retail sales data uncovering product performance, sales trends, and customer behavior patterns:
- Analyzed 1,000+ transactions across 3 branches
- Performed exploratory data analysis on 15 data dimensions
- Identified revenue drivers and top-performing product lines
- Segmented customer base by type, demographics, and purchase patterns
- Analyzed temporal patterns (time of day, day of week, seasonality)
Skills Demonstrated: Data wrangling, Feature engineering, Aggregations, Subqueries, Conditional logic, Date functions, Comparative analysis
- Aggregation functions (SUM, AVG, COUNT, GROUP BY, HAVING)
- Date and time functions (DAYNAME, MONTHNAME) for feature engineering
- Conditional logic (CASE statements)
- Subqueries and nested queries for comparative analysis
- WHERE clauses and filtering for granular analysis
- Exploratory Data Analysis (EDA)
- Business insight derivation
- Performance benchmarking
- Temporal trend analysis
- Customer segmentation
- Schema design with appropriate constraints
- Data type optimization
- Data integrity validation
- NULL value handling
- Database: MySQL
- Languages: SQL
- Data Formats: CSV, SQL scripts
- Version Control: Git
Each project directory contains:
- Detailed README with project overview and business questions
- Complete SQL implementation with all queries
- Raw data files (CSV format)
- Query examples organized by analysis category
-
Clone the repository:
git clone https://github.com/theshoaibakthar/SQL-Projects.git
-
Navigate to a project directory:
cd WalmartSalesAnalysis -
Import the data into your SQL database and execute the analysis queries
-
Refer to the project README for detailed documentation and business questions
Data Wrangling: Schema design, NULL validation, data cleaning
Feature Engineering: Temporal categorization (time_of_day, day_name, month_name) using date functions and CASE statements
Advanced Analysis: Comparative performance analysis, revenue segmentation, customer behavior patterns
Problem Solving: Translating business questions into efficient SQL queries
| Category | Skills |
|---|---|
| Querying | SELECT, WHERE, GROUP BY, HAVING, ORDER BY |
| Aggregation | SUM, AVG, COUNT, MIN, MAX with GROUP BY |
| Functions | Date functions, String functions, CASE logic |
| Analysis | Subqueries, Comparative queries, Temporal analysis |
| Design | Schema creation, Data type selection, Constraints |
- Implementation of window functions and CTEs
- Performance optimization and query execution plans
- Additional datasets and comparative analysis projects
For more information about these projects and my SQL expertise, feel free to reach out or explore the detailed project READMEs.
Last Updated: November 2025
This portfolio demonstrates practical SQL expertise in data analysis and business intelligence.