🏬 Retail Sales Data Warehouse Project

📌 SAP BW-inspired Architecture | MySQL | SQL ETL | Power BI Dashboard

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🚀 Overview

This project demonstrates a full end-to-end Data Warehouse and Business Intelligence solution using:

• MySQL for data modeling and ETL
• Power BI for reporting and visual analytics
• SAP BW/4HANA-inspired architecture for structure and methodology

It simulates a Retail business analytics system where raw transactional data flows through staging → dimensional modeling → fact table → semantic layer → dashboard KPIs.

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🧠 Architecture Summary

The design is aligned with principles used in enterprise BI platforms such as SAP BW/4HANA, including:

SAP BW/4HANA Concept	Equivalent in This Project
DataSource / ADSO Staging	stg_sales raw data table
InfoObjects	dim_customer, dim_product, dim_store, dim_date
ADSO (Fact Provider)	fact_sales
CompositeProvider / Semantic Layer	vw_sales_enriched
Reporting (BEx/ SAC)	Power BI Dashboard & SQL KPIs

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🛠️ Tech Stack

Component	Technology
Database	MySQL 8.0
ETL	SQL (LOAD DATA + transformation logic)
Modeling	Star Schema (Fact + Dimensions)
Reporting	Power BI (KPIs, charts, analytics)
Tools Used	VS Code, GitHub

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🔧 Schema Design (Star Model)

   dim_customer
        │
        │

dim_product ─ fact_sales ─ dim_store │ │ dim_date

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📂 Project Structure

Retail-DW-Product/ │ ├── data/ # CSV source data ├── sql/ # ETL + schema scripts │ ├── 01_create_schema.sql │ ├── 02_create_tables.sql │ ├── 03_load_data.sql │ ├── 04_create_views.sql │ └── 05_kpis.sql │ ├── docs/ │ ├── dashboard_preview.png # BI visualization sample │ └── retail_dw_dashboard_demo.mp4 # Walkthrough video │ ├── main.sql # Entry point to run full pipeline └── README.md

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📥 Data Flow

1. CSV raw data imported → stg_sales
2. Clean & transform data
3. Load into dimension tables
4. Load into fact_sales
5. Create Semantic View: vw_sales_enriched
6. Run analytical KPIs and reporting queries
7. Visualize in Power BI

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📊 Sample KPIs (SQL)

KPI	Result Type
Total Revenue	💰 Scalar
Monthly Trend	📈 Timeseries
Top Products	🏆 Ranking
Revenue by Region	📍 Geo-based
Customer Segment Analysis	🧩 Category split

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🖥 Power BI Dashboard Preview

📌 Built on top of the semantic layer (vw_sales_enriched).

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🎥 Demo Video

📎 Full Walkthrough:
Retail Sales Analytics Dashboard

➡ docs/retail_dw_dashboard_demo.mp4.mp4

(If GitHub preview doesn't autoplay, download to view.)

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🧪 How to Run

1️⃣ Clone Repository

git clone https://github.com/<username>/Retail-DW-Product.git
cd Retail-DW-Product

 ### 1️⃣ Run MySQL Scripts

mysql -u root -p < sql/01_create_schema.sql
mysql -u root -p retail_dw < sql/02_create_tables.sql
mysql --local-infile=1 -u root -p retail_dw < sql/03_load_data.sql
mysql -u root -p retail_dw < sql/04_create_views.sql
mysql -u root -p retail_dw < sql/05_kpis.sql

## In PowerBI:
### Connect to : 

Server: localhost
Database: retail_dw
Table/View: vw_sales_enriched

✨ Thank you for viewing this project! ✨

#DataEngineering  #SQL  #SAPBW  #PowerBI  #BusinessIntelligence  #ETL  #Analytics