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📊 SQL for Data Analytics

👨‍💻 About Me

Hi, I'm Vedant Jamdade 🎓 B.Tech CSE Student 📊 Aspiring Data Analyst

This repository is part of my journey to become a Data Analyst, where I practice and implement SQL concepts used in real-world data analysis.


🎯 Project Objective

The goal of this repository is to:

  • Learn and practice SQL from basics to advanced
  • Understand how SQL is used in data analysis
  • Build strong problem-solving skills using SQL queries
  • Prepare for Data Analyst internships and interviews

🛠 Tools & Technologies

  • SQL (MySQL)
  • MySQL Workbench
  • Git & GitHub

📥 MySQL Workbench Installation Guide:

Download MySQL Installation Guide


📚 SQL Topics Covered

This repository covers SQL concepts from basic to advanced levels used in data analysis:

🔹 Fundamentals

  • SQL Commands (DDL, DML, DQL)
  • Data Types
  • Constraints (Primary Key, Foreign Key, NOT NULL, UNIQUE)

🔹 Data Querying

  • SELECT Statements
  • WHERE Clause (Data Filtering)
  • ORDER BY
  • GROUP BY
  • HAVING Clause

🔹 Data Analysis

  • Aggregation Functions (SUM, AVG, COUNT, MAX, MIN)
  • Data Exploration Techniques

🔹 Advanced SQL

  • Joins (INNER, LEFT, RIGHT)
  • Subqueries
  • Common Table Expressions (CTE)
  • Window Functions
  • Frame Clause (ROWS / RANGE)
  • CASE Statements

🔹 Additional Concepts

  • Set Operators (UNION, INTERSECT)
  • String Functions

📊 Skills Demonstrated

  • Data Filtering (WHERE)
  • Aggregations (SUM, AVG, COUNT)
  • Joins (INNER, LEFT, RIGHT)
  • Subqueries
  • Window Functions
  • Data Exploration Techniques

🚀 Learning Outcome

Through this repository, I have:

  • Built a strong foundation in SQL
  • Learned how to analyze and explore data
  • Practiced real-world query scenarios
  • Improved problem-solving skills

📌 Future Improvements

  • Add real-world datasets
  • Add SQL projects (Retail, Sales, E-commerce)
  • Add interview-based SQL questions

⭐ If you find this repository helpful, please consider giving it a star!

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Comprehensive SQL repository covering fundamental to advanced concepts used in data analysis, including data filtering, aggregations, joins, subqueries, window functions, and data exploration techniques.

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