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