I performed a comprehensive analysis of a Superstore dataset to uncover sales trends, customer behavior, and product performance insights. The project included data cleaning, exploratory data analysis (EDA), and interactive visualizations to support data-driven decision-making.
Key tasks completed:
Cleaned and prepared raw sales data for analysis using Excel and Python (Pandas).
Conducted exploratory data analysis (EDA) to identify key patterns in sales, profit, and customer segments.
Built interactive dashboards using Power BI to visualize:
Sales by region, category, and sub-category
Profit trends over time
Top-performing products and loss-generating items
Generated actionable insights to optimize inventory and marketing strategies.
Tools used: Excel, Python (Pandas, Matplotlib, Seaborn), Power BI
Key tasks completed:
Cleaned and prepared raw sales data for analysis using Excel and Python (Pandas).
Conducted exploratory data analysis (EDA) to identify key patterns in sales, profit, and customer segments.
Built interactive dashboards using Power BI to visualize:
Sales by region, category, and sub-category
Profit trends over time
Top-performing products and loss-generating items
Generated actionable insights to optimize inventory and marketing strategies.
Tools used: Excel, Python (Pandas, Matplotlib, Seaborn), Power BI