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Gungn1r-G/README.md

👋 Hi, I'm Gitesh Kumar

Data Analyst • SQL • Python • Power BI

MS in Computing graduate focused on turning data into clear, useful analysis.

LinkedIn Email

👨‍💻 About Me

🎓 MS in Computing graduate
📊 Focused on Data Analytics & Business Intelligence
🔍 Working with SQL, Python, Excel, and Power BI
🗄️ Interested in data analysis, visualization, databases, and reporting
💻 Background in software development
📚 Currently strengthening my analytics stack through hands-on projects and practice

🛠️ Analytics & Tech Stack

📊 Data Analytics & BI

SQL Python Pandas Excel Power BI

🗄️ Databases

MySQL SQLite

⚙️ Development & Tools

Git GitHub Jupyter C Sharp

🚀 Featured Projects

📈 Global Superstore Sales & Profitability Analysis

SQL • Python • Pandas • Power BI

Analyzed 51K+ retail records to investigate regional performance, product profitability, and the relationship between discounting and unprofitable orders.

  • Cleaned and validated raw data using Python and SQL
  • Used SQL CTEs and window functions for analytical queries
  • Investigated regional and product-level profitability
  • Identified a 20%+ discount threshold associated with unprofitable orders
  • Presented findings through an interactive Power BI dashboard

➡️ Explore the project →

👥 IBM HR Employee Attrition Analysis

Excel • MySQL • Power BI • DAX

Analyzed employee data for 1,470 employees to identify patterns associated with workforce attrition and explore how factors such as job role, overtime, income, and tenure relate to employee turnover.

  • Cleaned and analyzed employee data using Excel and MySQL
  • Used PivotTables and SQL queries to investigate attrition across employee groups
  • Found 39.76% attrition among Sales Representatives
  • Identified 30.53% attrition among employees working overtime, compared with 10.44% for employees who did not
  • Built an interactive Power BI dashboard with DAX measures and cross-filtering to communicate key findings

➡️ Explore the project →

📂 More Projects

Check out my pinned repositories for additional work.

Pinned Loading

  1. Superstore-sales-analysis Superstore-sales-analysis Public

    Cleaned and analyzed a 51K-row retail dataset using Python, SQL, and Power BI to uncover profitability drivers including a 20%+ discount threshold that flips orders unprofitable.

    Jupyter Notebook

  2. IBM-HR-Attrition-Analysis IBM-HR-Attrition-Analysis Public

    End-to-end HR attrition analysis using Excel, MySQL, and Power BI on the IBM HR Employee Attrition dataset identifying which employee segments (job role, overtime, tenure) actually drive turnover, …

  3. Library-Management-System Library-Management-System Public

    A Flask + SQLAlchemy library management system with a normalized (3NF) relational database, transactional loan logic to prevent double-booking, and a SQL-based analytics dashboard.

    Python

  4. Customer-Churn-Prediction Customer-Churn-Prediction Public

    Predicting customer churn using SQL, Python (logistic regression), and Power BI and ,identifies at-risk customers to support targeted retention efforts.

    Jupyter Notebook