https://github.com/ayushman0511/data-warehouse-project1
A comprehensive guide to building a data warehouse with SQL Server, including ETL processes, data modeling, and analytics.
https://github.com/ayushman0511/data-warehouse-project1
data data-ana data-anal data-cleaning data-enginee data-lakehou datalake datasci dataware datawarehouse datawarehousi etl etl-job etl-pipeline medallion sql sql-quer sql-query sql-server sqlserver
Last synced: 4 months ago
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A comprehensive guide to building a data warehouse with SQL Server, including ETL processes, data modeling, and analytics.
- Host: GitHub
- URL: https://github.com/ayushman0511/data-warehouse-project1
- Owner: Ayushman0511
- Created: 2025-05-27T14:47:35.000Z (5 months ago)
- Default Branch: main
- Last Pushed: 2025-06-05T18:56:31.000Z (4 months ago)
- Last Synced: 2025-06-26T14:05:07.176Z (4 months ago)
- Topics: data, data-ana, data-anal, data-cleaning, data-enginee, data-lakehou, datalake, datasci, dataware, datawarehouse, datawarehousi, etl, etl-job, etl-pipeline, medallion, sql, sql-quer, sql-query, sql-server, sqlserver
- Language: TSQL
- Homepage:
- Size: 3.29 MB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# 📊Data-Warehouse-Project1
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 also highlights industry best practices in data engineering and analytics that I have learnt so far.
---
## 🏗️ 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.
---
## 📖 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.
---
## 🛠️ Important Links & Tools:
Everything is for Free!
- **[Datasets](dataset/):** Access to the project dataset (csv files).
- **[SQL Server Express](https://www.microsoft.com/en-us/sql-server/sql-server-downloads):** Lightweight server for hosting your SQL database.
- **[SQL Server Management Studio (SSMS)](https://learn.microsoft.com/en-us/sql/ssms/download-sql-server-management-studio-ssms?view=sql-server-ver16):** GUI for managing and interacting with databases.
- **[Git Repository](https://github.com/):** Set up a GitHub account and repository to manage, version, and collaborate on your code efficiently.
- **[DrawIO](https://www.drawio.com/):** Design data architecture, models, flows, and diagrams.
- **[Notion](https://www.notion.com/templates/sql-data-warehouse-project):** Get the Project Template from Notion
- **[Notion Project Steps]([https://thankful-pangolin-2ca.notion.site/SQL-Data-Warehouse-Project-16ed041640ef80489667cfe2f380b269?pvs=4](https://www.notion.so/Data-Warehouse-Project-20091951d87b8040a337ec3dfdcd0282?source=copy_link)):** Access to All Project Phases and Tasks.
---
## 🚀 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**
These insights empower stakeholders with key business metrics, enabling strategic decision-making.
## 📂 Repository Structure
```
data-warehouse-project/
│
├── dataset/ # Raw datasets used for the project (ERP and CRM data)
│
├── docs/ # Project documentation and architecture details
│ ├── ETL.png # Draw.io file shows all different techniquies and methods of ETL
│ ├── Architecture of DWH.png # Draw.io file shows the project's architecture
│ ├── data_catalog.md # Catalog of datasets, including field descriptions and metadata
│ ├── Data_Flow.png # Draw.io file for the data flow diagram
│ ├── data_models.png # Draw.io file for data models (star schema)
│ ├── naming_conventions.md # Consistent naming guidelines for tables, columns, and files
│
├── scripts/ # SQL scripts for ETL and transformations
| ├── init_database.sql # Script to initialize the bronze, silver and gold schemas & database (`datawarehouse`).
│ ├── bronze/ # Scripts for extracting and loading raw data
| ├── ddl_bronze.sql # Script that defimes the metadata(schema) for loading the files.
| ├── procedure_load_bronze.sql # Script that bulk-loads the data from the local device & provides debugging assist and execution time informations.
│ ├── silver/ # Scripts for cleaning and transforming data
| ├── ddl_silver.sql # Script that defimes the metadata(schema) for loading the files.
| ├── procedure_load_silver.sql # Script that transforms & cleans the data, then loads it from the bronze layer in to silver layer. Also provides debugging assist and execution time informations.
│ ├── gold/ # Scripts for creating analytical models
│ ├── ddl_gold.sql # Script for creating views and provide analytical abilities for the data from silver layer.
|
├── tests/ # Test scripts and quality files
│
├── README.md # Project overview and instructions
```
---
## 🌟 About Me
Hi there! I'm Ayushman Bhargav. My field of interest include Internet of Things(IoT), Data Science and Machine Learning(AI/ML) , working towards upgrading my skills and knowledge through a combined learning of Theoretical Concepts as well as using practical projects to advance my learning.
Let's stay in touch! Feel free to connect with me via LinkedIn:
