🏭Data Warehouse and Analytics Project

Welcome to my SQL Data Warehouse & Analytics Project! 🚀

This project showcases a complete end-to-end solution for building a modern data warehouse using SQL Server, transforming raw data into business-ready insights. Designed as a portfolio project, it demonstrates my hands-on skills in data engineering, ETL pipeline development, and analytics.

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📌 Overview

This repository presents a structured approach to data warehousing, adhering to the Medallion Architecture:

• 🟤 Bronze Layer – Stores raw data as-is from the source systems. Data is ingested from CSV Files into SQL Server Database.

• ⚪ Silver Layer – This layer includes data cleansing, standardization, and normalization processes to prepare data for analysis.

• 🟡 Gold Layer – Houses business-ready data modeled into a star schema required for reporting and analytics.

With data sourced from ERP and CRM systems (CSV format), I implemented ETL pipelines, created fact and dimension tables, and generated insights on customer behavior, product performance, and sales trends.

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🧱 Features

• 🏗️ Medallion Architecture applied in SQL Server

• 🔄 ETL Pipelines for ingestion, cleaning, transformation, and modeling

• 🌐 Star Schema Design (Fact & Dimension tables)

• 📊 Analytics-ready tables supporting reporting needs

• 📚 Documentation for architecture, flow, and schema

• 💡 SQL-based reporting for key business metrics

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📂 Project Structure

sql-data-warehouse-project/
│
├── datasets/                           # Raw CSV files from ERP and CRM
│
├── docs/                               # All documentation and visuals
│   ├── data_architecture_diagram.png   # Visual representation of architecture
│   ├── data_catalog.md                 # Gold Layer: Tables and column descriptions
│   ├── etl.drawio                      # ETL flow diagram
│   ├── data_models.drawio              # Star schema model
│   ├── naming-conventions.md           # Standards for naming
│
├── scripts/
│   ├── bronze/                         # Ingest raw data
│   ├── silver/                         # Transform & clean data
│   ├── gold/                           # Create business-level models
│
├── tests/                              # SQL validation and quality checks
│
├── README.md                           # This file
└── requirements.txt                    # Tools & dependencies

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🧪 Tech Stack & Tools

• SQL Server Express – Backend DBMS

• SSMS (SQL Server Management Studio) – GUI for development

• Draw.io – Architecture and data modeling diagrams

• Git & GitHub – Version control and collaboration

• Notion – Project planning and documentation

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📊 Key Insights Delivered

• 📈 Customer Behavior Analysis

• 🛒 Product Performance Metrics

• 💰 Sales Trend Insights

Each of these was enabled through optimised SQL queries over the Gold Layer, empowering stakeholders with actionable intelligence.

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✅ What I Learned

• Real-world implementation of Medallion Data Architecture

• Building efficient and reusable ETL processes

• Hands-on practice with dimensional modeling

• Writing performant and readable SQL queries for analytics

• Importance of clear documentation and naming conventions

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🙋‍♂️ About Me

Hi! I’m Aayush Yagol, a data enthusiast who loves turning raw data into insights that drive business decisions. This project was an exciting deep dive into data engineering, and I look forward to building more solutions that make working with data fun, efficient, and impactful.

📫 Let’s connect:

⭐ If you found this project helpful or inspiring, feel free to star the repo and connect with me!⭐