https://github.com/moshora99/sql-data-warehouse-project
Build modern data warehouse with mysql, Including ETL processes, data modeling and analytics
https://github.com/moshora99/sql-data-warehouse-project
data-analysis data-engineering data-science database datawarehouse datawarehousing etl scheme sql sql-query sql-server
Last synced: 3 months ago
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Build modern data warehouse with mysql, Including ETL processes, data modeling and analytics
- Host: GitHub
- URL: https://github.com/moshora99/sql-data-warehouse-project
- Owner: MoShora99
- License: mit
- Created: 2025-06-20T16:24:56.000Z (4 months ago)
- Default Branch: main
- Last Pushed: 2025-06-28T13:51:08.000Z (3 months ago)
- Last Synced: 2025-06-28T14:33:00.311Z (3 months ago)
- Topics: data-analysis, data-engineering, data-science, database, datawarehouse, datawarehousing, etl, scheme, sql, sql-query, sql-server
- Language: TSQL
- Homepage:
- Size: 32.2 KB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Data Warehouse and Analytics Project
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.
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## 🏗️ Data Architecture
The data architecture for this project follows Medallion Architecture **Bronze**, **Silver**, and **Gold** layers:
1. **Bronze Layer**: Stores raw data as-is from the source systems. Data is ingested from CSV Files into SQL Server Database.
2. **Silver Layer**: This layer includes data cleansing, standardization, and normalization processes to prepare data for analysis.
3. **Gold Layer**: Houses business-ready data modeled into a star schema required for reporting and analytics.
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## 📖 Project Overview
This project involves:
1. **Data Architecture**: Designing a Modern Data Warehouse Using Medallion Architecture **Bronze**, **Silver**, and **Gold** layers.
2. **ETL Pipelines**: Extracting, transforming, and loading data from source systems into the warehouse.
3. **Data Modeling**: Developing fact and dimension tables optimized for analytical queries.
4. **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
## 🚀 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 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.
---
### BI: Analytics & Reporting (Data Analysis)
#### Objective
Develop SQL-based analytics to deliver detailed insights into:
- **Customer Behavior**
- **Product Performance**
- **Sales Trends**