Final Course Project: End-to-End Business Performance Dashboard

🚀 Project Overview

This capstone project requires you to act as a Lead Data Analyst for a Global E-commerce firm. You will take a raw, messy dataset and move it through the entire pipeline: **Excel** (Cleaning) → **MySQL** (Querying) → **Power BI** (Visualization) to present actionable business insights.

Problem Statement

"Global-Mart" has noticed a decline in profits despite increasing sales. The CEO needs a comprehensive dashboard to identify which regions, products, and customer segments are underperforming and why. The current data is scattered across messy CSVs and database tables.

Phase 1: Excel Data Cleaning

• Import 50,000 rows of raw transaction data.
• Use **Power Query** to fix date formats and remove nulls in the "Discount" column.
• Create a calculated column for **Net Profit**.
• Export the cleaned data as a CSV ready for database import.

Phase 2: MySQL Analytical Querying

• Create a database global_mart_db and import the cleaned CSV.
• Write a SQL script using **CTEs** to identify the "Top 10 High-Value Customers".
• Use **Joins** to combine the Sales table with a Product Category table.
• Export the result set as the primary data source for Power BI.

Phase 3: Power BI Modeling & Visualization

• Import the SQL result set into Power BI Desktop.
• Create a **Star Schema** by linking Sales to a Date Dimension table.
• Write **DAX Measures** for: Total Revenue, Profit Margin %, and YoY Growth.
• Design a multi-page dashboard:
  1. Executive Summary: High-level KPIs and Map.
  2. Product Analysis: Bar charts showing category performance.
  3. Customer Insights: Slicers and Scatter plots for behavior.

Final Deliverable

• The cleaned Excel file (.xlsx).
• The SQL Script file (.sql).
• The Power BI Dashboard file (.pbix).
• A brief **Executive Summary** (PDF) listing 3 key recommendations (e.g., "Reduce discounts in the North region").

Evaluation Criteria

Skill Area	Weight
Data Cleaning Accuracy (Excel)	20%
Advanced SQL Logic (Joins/Aggregates)	25%
Data Modeling Excellence (Star Schema)	25%
Visual Storytelling and UI/UX	20%
Business Insight Quality	10%

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