This project demonstrates a comprehensive data warehousing solution, involving the building of a data warehouse that will help data analysts with finding actionable insights in data. Designed as a portfolio project, it highlights industry best practices in data engineering.
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.
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
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.
data-warehouse-project/
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├── datasets/ # Raw datasets used for the project (ERP and CRM data)
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├── docs/ # Project documentation and architecture details
│ ├── data_architecture.drawio # Draw.io file shows the project's architecture
│ ├── data_catalog.md # Catalog of datasets, including field descriptions and metadata
│ ├── data_flow_diagram.drawio # Draw.io file for the data flow diagram
│ ├── data_model.drawio # Draw.io file for data models (star schema)
│ ├── naming-conventions.md # Consistent naming guidelines for tables, columns, and files
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├── 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
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├── tests/ # Test scripts and quality files
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├── README.md # Project overview and instructions
├── LICENSE # License information for the repository
This project is licensed under the MIT License.
Credits: This project was built as a hands-on learning implementation based on the data engineering tutorial by Data with Baraa . While the architecture design and core data requirements follow the tutorial, all SQL scripting, pipeline implementation, database setup, and local troubleshooting were executed entirely by me.
Hi there! I'm Molo Munyansanga. I’m an IT professional and passionate data enthusiast who loves working with data.
Let's stay in touch! Feel free to connect with me on:
