Skip to content

README.md

Latest commit

 

History

History
127 lines (88 loc) · 5.16 KB

README.md

File metadata and controls

127 lines (88 loc) · 5.16 KB

Data Warehouse and Analytics Project

Welcome to my Data Warehouse and Analytics Project repository. This project demonstrates my comprehensive data warehousing and analytics solution, from building a data warehouse to generating actionable insights. Designed as a portfolio project, it highlights industry best practices in data engineering and analytics.

🏗️ Data Architecture

The data architecture for this project follows Medallion Architecture with Bronze, Silver, and Gold layers:

Layer Description
Bronze Stores raw data as-is from source systems. Data is ingested from CSV files into SQL Server.
Silver Includes data cleansing, standardization, and normalization to prepare data for analysis.
Gold Houses business-ready data modeled into a star schema required for reporting and analytics.

📖 Project Overview

This project involves:

  • Data Architecture: Designing a Modern Data Warehouse using Medallion Architecture (Bronze, Silver, and Gold layers)
  • ETL Pipelines: Extracting, transforming, and loading data from source systems into the warehouse
  • Data Modeling: Developing fact and dimension tables optimized for analytical queries
  • Analytics & Reporting: Creating SQL-based reports and dashboards for actionable insights

🎯 Skills Showcased

This repository is my introduction to Data Engineering:

  • SQL Development
  • Data Architecture
  • Data Engineering
  • ETL Pipeline Development
  • Data Modeling
  • Data Analytics

🛠️ Tools & Resources

  • Datasets: CSV files for the project dataset
  • SQL Server Express: Lightweight server for hosting your SQL database
  • SSMS: GUI for managing and interacting with databases
  • Git: Version control and collaboration
  • DrawIO: Design data architecture, models, flows, and diagrams
  • Notion: Project template and task management

🚀 Project Requirements

Building the Data Warehouse (Data Engineering)

Objective: Develop a modern data warehouse using SQL Server to consolidate sales data, enabling analytical reporting and informed decision-making.

Specifications:

  • Data Sources: Import data from two source systems (ERP and CRM) provided as CSV files
  • Data Quality: Cleanse and resolve data quality issues prior to analysis
  • Integration: Combine both sources into a single, user-friendly data model for analytical queries
  • Scope: Focus on the latest dataset only; historization of data is not required
  • Documentation: Provide clear documentation of the data model for business stakeholders and analytics teams

BI: Analytics & Reporting (Data Analysis)

Objective: Develop SQL-based analytics to deliver detailed insights into:

  • Customer Behavior
  • Product Performance
  • Sales Trends

These insights empower stakeholders with key business metrics, enabling strategic decision-making.

📌 Project Management

The project was managed via notion, here is the project task tracker and breakdown;

Notion

📂 Repository Structure

data-warehouse-project/
│
├── datasets/                           # Raw datasets (ERP and CRM data)
│
├── docs/                               # Project documentation and architecture
│   ├── etl.drawio                      # ETL techniques and methods diagram
│   ├── data_architecture.drawio        # Project architecture diagram
│   ├── data_catalog.md                 # Dataset catalog with field descriptions
│   ├── data_flow.drawio                # Data flow diagram
│   ├── data_models.drawio              # Data models (star schema)
│   └── naming-conventions.md          # Naming guidelines for tables, columns, and files
│
├── scripts/                            # SQL scripts for ETL and transformations
│   ├── bronze/                         # Scripts for extracting and loading raw data
│   ├── silver/                         # Scripts for cleaning and transforming data
│   └── gold/                           # Scripts for creating analytical models
│
├── tests/                              # Test scripts and quality files
│
├── README.md                           # Project overview and instructions
├── LICENSE                             # License information
├── .gitignore                          # Git ignore rules
└── requirements.txt                    # Project dependencies

☕ Stay Connected

Let's stay in touch! Feel free to connect with me:

LinkedIn

🛡️ License

This project is licensed under the MIT License. You are free to use, modify, and share this project with proper attribution.