Sales performance analysis and dashboard

Sales Performance Analysis: Summary
1. Overview
End-to-end data analytics project using Python, SQL, and Power BI
Dataset: Superstore sales data, about 9,800 records
Covers orders, customers, products, regions, and shipping
Goal: turn raw sales data into clear business insights

2. Process

Cleaned the data in Python (Pandas): fixed missing values, duplicates, and data types
Created new features: shipping days, month, quarter, and season
Explored the data with EDA in Python
Queried the data with SQL to answer business questions
Compared performance across regions, categories, segments, and time periods

3. Dashboard and Findings

Interactive, dark-themed Power BI dashboard
Filters for year, region, and category
Key results:
$2.26M total sales
5K orders and 793 customers
West is the top region
Technology is the top category (about 37%)
Consumers contribute about 51% of revenue
Autumn is the strongest season

4. Value and Recommendations

Focus marketing and stock on top products and regions
Investigate and improve weaker regions and products
Plan inventory and promotions around seasonal peaks
Shows raw data can become practical business decisions
Works well as a portfolio piece for freelance clients