Welcome to the Data Warehouse and Analytics Project repository! 🚀
This project demonstrates a 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.
The data architecture for this project follows Medallion Architecture Bronze, Silver, and Gold layers:
- 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.
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.
🎯 This repository is an excellent resource for professionals and students looking to showcase expertise in:
- SQL Development
- Data Architect
- Data Engineering
- ETL Pipeline Developer
- Data Modeling
- Data Analytics
- Datasets: Access to the project dataset (csv files).
- SQL Server Express: Lightweight server for hosting your SQL database.
- SQL Server Management Studio (SSMS): GUI for managing and interacting with databases.
- Git Repository: Set up a GitHub account and repository to manage, version, and collaborate on your code efficiently.
- DrawIO: Design data architecture, models, flows, and diagrams.
- Notion: Project Template from Notion
- Notion Project Steps: Access to All Project Phases and Tasks.
Develop a modern data warehouse using SQL Server to consolidate sales data, enabling analytical reporting and informed decision-making.
- 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 designed for analytical queries.
- Scope: Focus on the latest dataset only; historization of data is not required.
- Documentation: Provide clear documentation of the data model to support both business stakeholders and analytics teams.
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.
SQL-Data-Warehouse-Project/
│
├── datasets/ # Raw datasets used for the project (ERP, CRM, etc.)
│
├── docs/ # Project documentation and architecture details
│ │
│ ├── drawio_files/ # Editable Draw.io diagrams (source files)
│ │
│ ├── ETL.png # Exported PNG: ETL workflow diagram
│ ├── data_architecture.png # Exported PNG: DW architecture
│ ├── data_flow.png # Exported PNG: Data flow diagram
│ ├── data_integration.png # Exported PNG: Data integration steps / pipelines
│ ├── data_model.png # Exported PNG: Star Schema data model
│ ├── data_layers.pdf # PDF describing Bronze / Silver / Gold layers
│ │
│ ├── data_catalog.md # Dataset metadata, field descriptions, data types
│ ├── naming_conventions.md # Naming rules for tables, columns, files, layers
│
├── scripts/ # SQL scripts and processing code
│ ├── bronze/ # Extraction & raw ingestion scripts
│ ├── silver/ # Cleaning, standardization & enrichment scripts
│ ├── gold/ # Analytical model creation (fact/dim tables)
│
├── tests/ # Data quality tests, schema validation, pipeline tests
│
├── README.md # Project overview, setup, usage instructions
└── LICENSE # License information for the repository
This project is licensed under the MIT License. You are free to use, modify, and share this project with proper attribution.