Ebay Regional Sales Analysis

Project Insights

The objective was to integrate and transform raw data from multiple Excel files into meaningful business insights. Through data modeling, cleaning, and analysis, key patterns such as sales performance, product trends, and customer behavior were identified. This project demonstrates how structured data workflows and visualization tools can convert scattered data into actionable insights for better decision-making.

# End-to-End Analytics Pipeline
  Raw Excel Files → Data Understanding → ER Modeling → Data Merging (Pandas)
            → Data Cleaning & Wrangling → EDA (Matplotlib & Seaborn)
                  → Data Transformation → Power BI Visualization → Business Insights

# End-to-End Analytics Pipeline
  Raw Excel Files → Data Understanding → ER Modeling → Data Merging (Pandas)
            → Data Cleaning & Wrangling → EDA (Matplotlib & Seaborn)
                  → Data Transformation → Power BI Visualization → Business Insights

# End-to-End Analytics Pipeline
  Raw Excel Files → Data Understanding → ER Modeling → Data Merging (Pandas)
            → Data Cleaning & Wrangling → EDA (Matplotlib & Seaborn)
                  → Data Transformation → Power BI Visualization → Business Insights

Key Features

• Data integration from multiple Excel sources

• Entity Relationship Modeling (ERM) for structured understanding

• Data cleaning and wrangling using Pandas

• Exploratory Data Analysis (EDA) using Matplotlib and Seaborn

• Identification of key trends in sales, products, and customer behavior

• Interactive dashboards and insights using Power BI

Tech Stack

• Python (Pandas, Matplotlib, Seaborn)

• Power BI

• Jupyter Notebook

  
  

Dashboard