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https://github.com/alefrp/properties_dbt
A DBT project for analyzing city property data.
https://github.com/alefrp/properties_dbt
data-analysis data-warehouse dbt python sql
Last synced: 2 days ago
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A DBT project for analyzing city property data.
- Host: GitHub
- URL: https://github.com/alefrp/properties_dbt
- Owner: AlefRP
- License: mit
- Created: 2024-04-05T11:56:58.000Z (7 months ago)
- Default Branch: main
- Last Pushed: 2024-06-19T17:21:44.000Z (5 months ago)
- Last Synced: 2024-06-20T05:56:25.904Z (5 months ago)
- Topics: data-analysis, data-warehouse, dbt, python, sql
- Homepage:
- Size: 8.79 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# City Properties Data Warehouse Using DBT
## Introduction
Welcome to the README for the DBT project aimed at simulating a Data Warehouse or Data Mart for city properties. This project, powered by dbtCore, is structured to facilitate the transformation, analysis, and understanding of property data within a city. It supports critical functions such as urban planning, taxation, and real estate analysis.
## Project Overview
This dbt project is designed to streamline the process of managing and transforming property data, ensuring a scalable and maintainable architecture. It leverages dbtCore for best practices in data modeling, version control, and automated testing.
## Getting Started
### Prerequisites
- dbtCore installed in your working environment
- Access to the relevant data source(s), such as a SQL database
### Installation
1. Clone this repository to your local machine or workspace.
2. Ensure dbtCore is installed and configured properly.
3. Update the `dbt_project.yml` file with your database connection details.
## Project Structure
- `models/`: Contains SQL files for dbt models, which define the transformed data structures for analysis.
- `stg_models/`: Staging models for initial data transformations.
- `dim_models/`: Dimension models for detailed analytical perspectives.
- `fact_models/`: Fact models that contain the core business metrics.
- `tests/`: Custom data validation tests to ensure data integrity.
- `macros/`: Reusable pieces of code for dynamic SQL generation in dbt models.
- `data/`: Directory for static data files, if used in the project.
- `dbt_project.yml`: The main project configuration file.
## Usage
After setting up your project, you can run dbt commands to execute models, run tests, and generate documentation:
```bash
dbt run # Runs your dbt models
dbt test # Executes tests defined in the `tests/` directory
dbt docs generate # Generates documentation for your project
dbt docs serve # Serves the generated documentation on a local web server
```
## License
This project is licensed under the MIT License - see the [LICENSE.md](LICENSE.md) file for details.