Industry-Ready SQL | Data Analysis | Business Querying Portfolio
Showcasing complex SQL queries, real-world datasets, performance tuning, and analytical insights
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## 📌 Repository Overview
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Domain : Data Analytics & Database Management
Technology : SQL (Advanced Level)
Databases : MySQL | PostgreSQL | SQL Server
Total Projects : 12+ Real-World SQL Projects
Focus Area : Queries | Joins | Subqueries | Optimization
Approach : Business-Oriented | Hands-on | Interview-Focused
Outcome : Job-Ready SQL Analyst Profile
This repository contains advanced SQL projects designed to demonstrate:
- Strong command over relational databases
- Ability to solve real-world business problems
- Writing optimized & readable SQL queries
- Analytical thinking using structured data
- Production-level SQL practices
📡 Live Repository Activity
📊 Automatically updated GitHub engagement indicators
💡 Perfect for recruiters, mentors & peer reviews
- Write complex SQL queries
- Solve business analytics problems
- Implement joins, subqueries & CTEs
- Perform data cleaning using SQL
- Apply window functions
- Optimize queries for performance
- Prepare interview-ready SQL solutions
| Industry Requirement | SQL Skill Applied |
|---|---|
| Data Retrieval | SELECT, WHERE, ORDER BY |
| Data Aggregation | GROUP BY, HAVING |
| Complex Relationships | INNER / LEFT / RIGHT / FULL JOIN |
| Advanced Analytics | Window Functions, CTEs |
| Business Logic | CASE WHEN, Subqueries |
| Performance Tuning | Indexing & Query Optimization |
| Data Quality | Cleaning & Validation Queries |
flowchart TB
A[Business Problem] --> B[Database Understanding]
B --> C[Data Cleaning Queries]
C --> D[Joins & Relationships]
D --> E[Aggregations & KPIs]
E --> F[Advanced SQL Logic]
F --> G[Query Optimization]
G --> H[Insights & Reporting]
classDef phase fill:#020617,color:#ffffff,stroke:#38bdf8,stroke-width:2px
class A,B,C,D,E,F,G,H phase
flowchart LR
A[Basic Queries]:::basic --> B[Filtering & Sorting]:::basic
B --> C[Joins]:::intermediate
C --> D[Subqueries & CTEs]:::intermediate
D --> E[Window Functions]:::advanced
E --> F[Optimization]:::advanced
F --> G[Business Analytics]:::deploy
classDef basic fill:#ecfeff,color:#020617,stroke:#06b6d4,stroke-width:2px
classDef intermediate fill:#fef3c7,color:#78350f,stroke:#f59e0b,stroke-width:2px
classDef advanced fill:#ede9fe,color:#4c1d95,stroke:#8b5cf6,stroke-width:2px
classDef deploy fill:#dcfce7,color:#14532d,stroke:#22c55e,stroke-width:2px
📁 Project_Name/
│
├── 📊 dataset.sql / dataset.csv
├── 🗄️ database_schema.sql
├── 🧠 queries.sql
├── 📄 problem_statement.md
├── 📈 insights.md
└── 📑 README.md
- Joins (All Types)
- Subqueries & Nested Queries
- Common Table Expressions (CTEs)
- Window Functions
- CASE Statements
- Date & Time Functions
- Data Cleaning Queries
- KPI Calculations
| Tool | Usage |
|---|---|
| SQL | Data Querying & Analysis |
| MySQL | Relational Database |
| PostgreSQL | Advanced SQL & Analytics |
| Excel / CSV | Dataset Preparation |
| GitHub | Version Control & Portfolio |
Ashwin Ananta Panbude Data Analyst | BI Developer | Faculty
This repository demonstrates advanced SQL expertise through real-world, business-driven projects. It reflects strong analytical thinking, database mastery, and interview-ready SQL skills, aligned with Data Analyst, SQL Developer & BI roles.