SCENTED_DW

A dimensional data warehouse project designed to model and analyze fragrance-related data using a star schema architecture. This project reflects governance-first engineering, symbolic clarity, and maintainable design principles.

🧱 Schema Overview

• Fact Table: FactFragranceRating — captures user ratings and load dates
• Dimensions:
  • DimFragrance: fragrance metadata (name, brand, gender)
  • DimBrand, DimGender, dim_year: supporting attributes
  • DimNote, DimAccord: scent taxonomy
• Bridge Tables:
  • BridgeFragranceNote: many-to-many relationship with ordered notes
  • BridgeFragranceAccord: many-to-many relationship with ordered accords

🗺️ Schema Diagram

🧠 Features

• Designed in SQL Server 2022
• Includes stored procedures for dimension and fact table population
• Surrogate keys and referential integrity enforced
• Supports analytical slicing by brand, gender, scent profile, and release year

🎯 Purpose

This project demonstrates:

• Dimensional modeling for catalog-style data
• ETL logic using stored procedures
• Governance-first design for maintainability and auditability
• Symbolic and branded alignment in technical architecture

🚀 Next Steps

• Extend with reporting layer (Power BI or SSRS)
• Add sample data and query examples
• Integrate with resume_app for cross-project analytics