SQL Data Warehouse Project

📖 Overview

This project implements a data warehouse using a layered architecture:

• Bronze Layer – Raw source data as loaded from external systems.
• Silver Layer – Cleaned, transformed, and standardized data.
• Gold Layer – Business-level data model (dimensions & facts) for analytics and reporting.

It demonstrates ETL best practices, data cleansing, and dimensional modeling using SQL Server.

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🏗️ Architecture

• Bronze Layer: Direct import of CSV files and other raw sources.
• Silver Layer: Business rules, data quality checks, deduplication, and transformations.
• Gold Layer: Final star schema with fact and dimension tables.

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📂 Repository Structure

Folder / File	Description
datasets/	Sample CSV files used to populate the Bronze layer.
scripts/	SQL scripts for ETL processes and table creation.
docs/	Project documentation (data catalogs, diagrams, etc.).
tests/	Optional test queries or scripts for data validation.

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🗂️ Data Model (Gold Layer)

• gold.dim_customers – Customer dimension with demographic attributes.
• gold.dim_products – Product dimension with category & attribute details.
• gold.fact_sales – Sales fact table linking customers and products. Full column definitions are documented in docs/data_catalog.md.

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🚀 Getting Started

Prerequisites

• Microsoft SQL Server (2019 or later recommended)
• SQL Server Management Studio (SSMS) or Azure Data Studio
• Sufficient disk/memory to load sample datasets

Setup Steps

1. Clone this repository:

   git clone https://github.com/Islam-Almshamsheh/SQL-Data-Warehouse-Project.git