https://github.com/vasanthakumar70/elt-with-snowflake-and-dbt
This project builds an end-to-end data pipeline to process and analyze retail sales data.
https://github.com/vasanthakumar70/elt-with-snowflake-and-dbt
dbt snowflake sql
Last synced: 5 months ago
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This project builds an end-to-end data pipeline to process and analyze retail sales data.
- Host: GitHub
- URL: https://github.com/vasanthakumar70/elt-with-snowflake-and-dbt
- Owner: vasanthakumar70
- Created: 2024-12-09T11:09:23.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-12-09T11:19:00.000Z (over 1 year ago)
- Last Synced: 2025-04-05T06:43:41.867Z (about 1 year ago)
- Topics: dbt, snowflake, sql
- Homepage:
- Size: 7.81 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Retail Sales Analytics Pipeline with Snowflake and dbt
## Project Overview
This project demonstrates an end-to-end data engineering pipeline to process and analyze retail sales data. The pipeline leverages **Snowflake** for data warehousing and **dbt** for data transformation and modeling. The goal is to build a scalable analytics platform for generating actionable business insights.
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## Features
- **Data Ingestion**: Load raw sales, customer, product, and geography data into Snowflake.
- **Data Modeling**: Implement a Star Schema with fact and dimension tables.
- **Data Transformation**: Use dbt to clean, join, and enrich raw data.
- **Visualization**: Generate dashboards in Power BI/Tableau to analyze KPIs such as sales trends and customer behavior.
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## Tech Stack
- **Snowflake**: Cloud-based data warehouse.
- **dbt**: Data transformation and modeling.
- **Git**: Version control for dbt models.
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## Data Workflow
1. **Ingest Raw Data**: Load data files into Snowflake using stages and the COPY command.
2. **Transform Data**: Use dbt to create models:
- **Staging**: Clean raw data.
- **Marts**: Fact and dimension tables in a Star Schema.
3. **Analyze Data**: Query Snowflake tables and visualize results in Power BI/Tableau.
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