Welcome to my Data Analytics Project Repository! This folder contains real-world projects where I apply SQL, Python, Excel, and Power BI to analyze data, extract insights, and create impactful visualizations that support data-driven decision-making.
- Tools Used: MySQL, Python (Pandas, Matplotlib, Seaborn), Power BI
- Summary: Analyzed over 40,000 stock market records from NIFTY50 across sectors like Finance, Energy, and Automobiles. Used SQL for data extraction, Python for trend detection, and Power BI for dashboard creation.
- Key Insights:
- Top 5 companies by Market Cap
- Sector-wise performance comparison
- Correlation between trading volume and stock price
- Tools Used: Power BI, DAX, SQL
- Summary: Built an interactive dashboard to monitor employee KPIs, commissions, and performance trends. Added filters and drill-downs for management-level insights.
- Tools Used: SQL, Power BI, Python
- Summary: Developed visual reports to analyze sales trends and customer behavior. Used machine learning (ARIMA) in Python for forecasting.
- SQL – Complex queries, joins, CTEs, window functions
- Python – Data cleaning, analysis, visualization
- Power BI – Dashboard creation, KPI cards, DAX
- Excel – Pivot tables, advanced functions
- Data Storytelling – Translating raw data into business value