GitHub - Tanu272004/E2E-Sales-Customer-Analytics-Dashboard-End-to-End-pipeline-with-Python-MySQL-Power-BI-: End-to-End Data Analytics Project covering ETL (Python + Azurite), MySQL data modeling, and interactive Power BI dashboards. Features:

Tanu272004 / E2E-Sales-Customer-Analytics-Dashboard-End-to-End-pipeline-with-Python-MySQL-Power-BI- Public

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End-to-End Data Analytics Project covering ETL (Python + Azurite), MySQL data modeling, and interactive Power BI dashboards. Features:

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Name		Name	Last commit message	Last commit date
Latest commit History 1 Commit
Azure Blob Storage.png		Azure Blob Storage.png
Azurite.png		Azurite.png
Customer Analysis.png		Customer Analysis.png
Data Source.png		Data Source.png
DrillThrough.png		DrillThrough.png
OrderMangementDashboard.pbix		OrderMangementDashboard.pbix
OrderMangementReport.pdf		OrderMangementReport.pdf
Product Trend.png		Product Trend.png
ReadMe.txt		ReadMe.txt
Requirement.txt		Requirement.txt
SQL_Queries.sql		SQL_Queries.sql
Sales Summary.png		Sales Summary.png
Script.py		Script.py
Shipping Details.png		Shipping Details.png
categories.csv		categories.csv
customers.csv		customers.csv
exchange_rates.csv		exchange_rates.csv
order_items.csv		order_items.csv
orders.csv		orders.csv
products.csv		products.csv
returns.csv		returns.csv
shipments.csv		shipments.csv
suppliers.csv		suppliers.csv
warehouses.csv		warehouses.csv

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# 📊 End-to-End Sales & Customer Analytics Dashboard

## 🚀 Project Overview
This project demonstrates a **complete data analytics pipeline** from data generation to business insights.  
It integrates **Python**, **Azurite (Azure Blob Storage Emulator)**, **MySQL**, and **Power BI** to deliver a fully interactive dashboard with drill-through capabilities.

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## 🛠 Tech Stack
- **Python** – Automated data generation & ETL
- **Azurite** – Local Azure Blob Storage simulation
- **MySQL** – Relational database for structured storage
- **Power BI** – Interactive dashboard & analytics

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## 📂 Project Workflow

1. **Data Generation (Python)**
   - Synthetic datasets for Customers, Orders, Shipments, and Products.
   - Controlled randomness to ensure realistic trends.

2. **Cloud Storage Simulation (Azurite)**
   - Datasets uploaded to local Azure Blob storage for cloud ETL simulation.

3. **Database Storage (MySQL)**
   - Normalized schema with primary & foreign key constraints.
   - SQL scripts for table creation and data insertion.

4. **Visualization (Power BI)**
   - KPI Cards: Total Revenue, Orders, Shipments.
   - Trend Charts: Monthly Revenue, Sales by Region.
   - Slicers: Interactive filtering by Date, Region, and Customer.
   - Drill-through Page: Detailed view of individual customer’s purchase history.

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## 📈 Key Insights
- **Top 10 Customers** contribute **₹X,XX,XXX (~45%)** of total revenue.
- **Region A** faces the highest shipment delays (~Y days avg.).
- **Category Electronics** dominates high-value purchases.
- Monthly revenue peaks observed in **November–December**.

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## 📸 Dashboard Preview
*(Add your dashboard screenshots here)*

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## 🧑‍💻 Setup Instructions

### 1️⃣ Clone Repository
```bash
git clone https://github.com/your-username/sales-customer-analytics.git
cd sales-customer-analytics

Lets Connect:
LinkedIn: https://www.linkedin.com/in/tanmay-sharma-800599373/
Github: https://github.com/Tanu272004/E2E-Sales-Customer-Analytics-Dashboard-End-to-End-pipeline-with-Python-MySQL-Power-BI-.git