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SQL-Sales-Marketing-DataWarehouse

A complete SQL-based data warehouse and ETL pipeline for Sales & Marketing analytics using Azure Data Factory, Azure Data Studio, and Azure SQL Database.
The project leverages OLTP → OLAP transformations and a star-schema design to provide advanced business intelligence (BI) insights into customer segmentation, sales optimization, discount impact, and demand forecasting.

Project Overview

This project focuses on building a Sales & Marketing Data Warehouse for Adventure Works Cycles.

It integrates multiple data sources into a centralized warehouse using Azure Data Factory (ADF) for ETL workflows, enabling advanced analytics such as:

  • Customer segmentation
  • Discount impact analysis
  • Demand forecasting
  • Trend and performance analysis

By transforming OLTP structures into a denormalized OLAP schema, the project enables efficient querying, high-performance analytics, and scalable reporting for business decision-making.

Objectives

  • Build a centralized Sales & Marketing Data Warehouse
  • Automate ETL pipelines using Azure Data Factory
  • Implement star-schema architecture for efficient querying
  • Support BI dashboards and data-driven decision-making
  • Provide insights into customer behavior, product sales, and profitability

Tools & Technologies

  • Azure Data Factory (ADF) – Orchestrating ETL pipelines
  • Azure Data Studio – Querying OLTP & OLAP databases
  • Azure SQL Database – Structured storage & schema design
  • SQL (DDL, DML, ETL scripting)
  • Star Schema & OLAP Cubes – BI-ready architecture

Repository Structure

SQL-Sales-Marketing-DataWarehouse/
│
├── ADF_ETL_Sales_Analytics/        # Core project folder
│   ├── AdvancedSales&MarketingDataWarehousingwithAzureReport.pdf   # Detailed project report
│   ├── README.md                   # Subfolder-level documentation
│
├── LICENSE                         # MIT License
├── README.md                       # Main project documentation