E-COMMERCE SALES DATA ANALYSIS 

E-Commerce Sales Data Analysis Using Power BI (2022–2024)

For this project, I conducted a comprehensive end-to-end sales data analysis using Power BI, working with a robust e-commerce dataset comprising over 102,000 purchase records and 21 data fields. The primary goal was to extract actionable insights around customer behavior, product performance, payment patterns, and sales trends to support data-driven decision-making and strategic planning.

Data Cleaning & Transformation (In Power BI)

All cleaning and transformation processes were meticulously executed within Power BI, without involving Excel at any stage. Using Power Query Editor, I:

• Removed irrelevant columns and fixed missing or inconsistent values.
  
  

• Standardized data formats across date, categorical, and numerical fields.
  
  

• Parsed and formatted fields like dates, locations, and product information for better usability.
  
  

Additionally, I created custom columns and calculated measures using DAX (Data Analysis Expressions) to enhance the dataset with business-relevant insights.

Calculated Columns & DAX Measures

Using DAX, I engineered several calculated columns and dynamic measures to provide in-depth sales intelligence. These included:

• Total Sales per Transaction
  
  

• Sales Contribution by Product Category
  
  

• Average Purchase Value per Customer
  
  

• Sales Trend Over Time (Monthly, Quarterly, Yearly)
  
  

• Top Performing Products & Categories
  
  

• Customer Retention and Churn Rate Analysis
  
  

• Revenue Distribution by Payment Method
  
  

• Promo Impact on Sales (With vs Without Discounts)
  
  

Each measure was tailored to uncover specific insights that aligned with the client’s business objectives.

Analysis & Visualization

With the cleaned and enriched dataset, I designed a visually engaging and intuitive dashboard that showcased key performance metrics and trends. The visualizations were organized for clarity and quick interpretation, including:

• Bar and Column Charts for top products, categories, and locations.
  
  

• Line and Area Charts to visualize sales performance over time.
  
  

• Donut and Pie Charts to represent customer demographics and payment breakdowns.
  
  

• Cards and KPIs highlighting key numbers like Total Revenue, Number of Orders, and Customer Count.
  
  

• Slicers and Filters for user-driven exploration by product, region, year, and other attributes.
  
  

The dashboard followed a custom theme featuring a studio-grade blend of purple and blue, contrasted with accents of yellow and white—designed to reflect a tech-savvy, professional aesthetic.

KEY INSIGHTS AND RECOMMENDATIONS

Final Outcome

This project demonstrates my ability to handle large-scale datasets entirely within Power BI, from raw data ingestion through to impactful visualization. By leveraging DAX and interactive storytelling, I transformed over 100K rows of raw transactional data into an actionable dashboard that empowers stakeholders with real-time insights into sales performance, customer behavior, and strategic opportunities.