SQL

📊 SQL Mastery: Data Analysis & Relational Database Design

🚀 Overview

This repository is a comprehensive showcase of SQL (Structured Query Language) skills. It features a wide range of queries from basic data retrieval to complex analytical reporting, demonstrating a deep understanding of extracting business insights from relational databases.

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🛠️ Core SQL Proficiencies

1. Advanced Data Filtering & Selection

• Precision Filtering: Mastery of WHERE clauses using IN, BETWEEN, LIKE (Wildcards), and Logical Operators (AND, OR, NOT).
• Data Refinement: Proficient use of DISTINCT, TOP, and TOP PERCENT for controlled data sampling.
• Null Handling: Specialized queries to manage and report on missing data using IS NULL and IS NOT NULL.

2. Complex Data Aggregation & Grouping

• Summary Statistics: Expert use of Aggregate Functions: COUNT(), SUM(), AVG(), MIN(), and MAX().
• Segmented Reporting: Advanced GROUP BY operations to categorize data (e.g., reporting vehicle counts per manufacturer).
• Post-Aggregation Filtering: Using HAVING to filter grouped results based on specific aggregate conditions.

3. Relational Data Modeling (Joins)

• Multi-Table Integration: Seamlessly combining data using INNER JOIN, LEFT JOIN, RIGHT JOIN, and FULL OUTER JOIN.
• Deep Relationships: Experience in joining 3+ tables to build comprehensive data views.
• Relational Logic: Using EXISTS and NOT EXISTS for high-performance subquery validation.

4. Computational Logic & Transformations

• Conditional Logic: Implementing complex CASE statements for data categorization (e.g., creating custom tax brackets or describing data in words).
• Arithmetic & Aliasing: Performing on-the-fly calculations (Yearly Salary, Age, Tax) and using AS for clean, readable output.
• Data Casting: Using CAST to handle floating-point divisions for accurate percentage calculations.

5. Database Objects & Optimization

• Views: Creating reusable and simplified data abstractions (e.g., ActiveEmployees, VehicleMasterDetails).
• Set Operations: Combining result sets using UNION and UNION ALL.
• Optimization: Utilizing TOP 1 inside EXISTS clauses to optimize query execution speed.

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📈 Real-World Business Scenarios Implemented

• Industry Analysis: Detailed reports on vehicle specifications, fuel types, and manufacturing trends.
• HR Reporting: Calculating employee salaries, bonuses, and status tracking.
• Performance Benchmarking: Identifying records that exceed or fall below Average benchmarks using subqueries.

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💡 How to use this folder

1. Open any .sql file to see the query logic.
2. Each script is documented with comments explaining the business requirement it solves.
3. Queries are optimized for SQL Server (T-SQL) environments.